Advertised Project Openings


Below are currently advertised UROP projects available to eligible undergraduates. All projects, regardless of mode (pay, credit, or volunteer) are expected to be worth MIT academic credit and be supervised by MIT faculty. Projects appear on this list in the order they have been received.

These projects do not represent all available UROPs as many faculty do not submit project listings for this site. Rather, they expect interested students to contact them based on their general research to discuss potential UROPs.

Available UROPs

9/21/18

Term: Fall/IAP

UROP Department, Lab or Center: Sloan School of Management (Course 15)

MIT Faculty Supervisor Name: Prof. Stuart Madnick

Project Title: Automated Support for Developing a Cyberspace Operations Functional Taxonomy

Project Description: CONTEXT: Cyberspace Operations (CO) Tasks/Actions can be undertaken for

Offence, Defense, and Security purposes. This project aims to develop a catalog of CO tasks in the form of a functionally decomposed taxonomy. The structure of the taxonomy is based analogy to the functional taxonomy used in traditional physical (air, land, maritime) domains of warfare as expressed in unclassified military doctrine publications. CO tasks will be obtained from cybersecurity and other cyber domain documents and from reasoning by analogy to the physical domains.

POTENTIAL STUDENT PROJECTS:

  • 1) Crawl a corpus of doctrine documents to extract a sample of tasks and identify the taxonomy structure for physical domains. While reviewing documents, identify rules that could be used for automated support for task extraction.
  • 2) Review cyber domain documents to extract sample tasks and make analogies to the physical domain tasks and taxonomy. Identify rules that could be used for automating analogy.
  • 3) Develop a knowledge base to store and access sample tasks, derived tasks, and taxonomy structure.
  • 4) Proof-of-concept experiments with Deep Learning methods (such as Tensorflow and PyTorch) to categorize and insert a list of tasks into the cyber domain taxonomy.
  • 5) Proof-of-concept experiments with Defeasible Logic Programming (such as Coherent Knowledge’s Ergo AI tools) rules-based methods for deriving and maintaining the cyber domain taxonomy.

Each student project will include a focused literature review and experiments with applying lessons from the literature.

RESEARCH GROUP

  • Cybersecurity at MIT Sloan
  • Interdisciplinary Consortium for Improving Critical Infrastructure
  • Cybersecurity

Prerequisites:

  • For projects 1 and 2, the ability to read and understand technical and military documents and to extract and organize key knowledge found.
  • For projects 3, 4, and 5, experience in programming with languages such as Python and Prolog and with data representation standards such as JSON.

Relevant URL:  https://cams.mit.ed

Contact Name: Allen Moulton, Research Scientist, Project Manager (amoulton@mit.edu)


9/21/18

Term: Fall/IAP

UROP Department, Lab or Center: Anthropology (Course 21A)

MIT Faculty Supervisor Name: Heather Paxson

Project Title: Relata: An Experimental Search Tool for Humanistic Scholarship

Project Description: This project proposes to combine human and machine intelligence to advance novel kinds of specialized search tools and recommender systems. In general, existing search tools and recommender systems are based on keyword or concept matching, ranking by popularity (e.g., citation counts and other measures of relevance, importance, and impact), and ranking by similarity (statistical correlation). The generic principles of popularity and similarity are often sufficient for simple applications like web searches, news feeds, and entertainment video recommendations. However, for more specialized applications such as scholarly discovery and scientific research, the

principles of popularity and similarity are frequently inadequate. Thus, we are designing an experimental search tool privileging critical perspectives for scholarly literature in the humanistic social sciences.

Prerequisites: Interest in anthropology and/or library sciences; coding skills helpful but not necessary.

Contact: Heather Paxson (paxson@mit.edu)


9/20/18

Term: Fall/IAP

UROP Department, Lab or Center: Materials Science and Engineering (Course 3)

MIT Faculty Supervisor Name: Michael J. Cima

Project Title: Implants for cost-effective and accessible intraperitoneal chemotherapy

Project Description: The Cima Lab is looking for an undergraduate researcher to participate in the development of novel drug delivery implants for local chemotherapy delivery to the abdomen to treat ovarian cancer metastases. Ovarian cancer is often diagnosed at a late stage after cancer cells have seeded organs throughout the abdominal cavity. Local chemotherapy delivered directly into the abdomen, known as intraperitoneal (IP) chemotherapy, has shown survival benefits in patients compared to traditional systemic IV chemotherapy. IP chemotherapy, however, requires specially trained staff to administer, is highly toxic, and has frequent complications related to its current method of administration. 

The Cima lab is developing a soft chemotherapy-releasing abdominal implant that will harness the benefits of local drug delivery and decrease the toxicity of current IP chemotherapy regimens. A student on this project will assist with prototyping implants, analyzing drug release profiles from the implants, and investigating the role of chemotherapy dosing on immune system function. An ideal student will be enthusiastic about learning techniques in device design, interested in expanding their general knowledge about translation biomedical devices, and committed to making an impact on the project.

Prerequisites: No experience is required. Training will be provided in all areas. We will give preference to candidates who can commit to working at least 12 hours per week during the academic year. We are offering academic credit for new UROPs. The position is available starting September 2018.

Contact: Kriti Subramanyam (kriti@mit.edu)


9/20/18

Term: Fall/IAP

UROP Department, Lab or Center: Materials Science and Engineering (Course 3)

MIT Faculty Supervisor Name: Michael J. Cima

Project Title: Implantable devices for tumor diagnosis and drug therapy

Project Description: The Cima Lab is looking for an undergraduate researcher to participate in the development of novel drug delivery implants for local chemotherapy delivery to the abdomen to treat ovarian cancer metastases. Ovarian cancer is often diagnosed at a late stage after cancer cells have seeded organs throughout the abdominal cavity. Local chemotherapy delivered directly into the abdomen, known as intraperitoneal (IP) chemotherapy, has shown survival benefits in patients compared to traditional systemic IV chemotherapy. IP chemotherapy, however, requires specially trained staff to administer, is highly toxic, and has frequent complications related to its current method of administration. 

The Cima lab is developing a soft chemotherapy-releasing abdominal implant that will harness the benefits of local drug delivery and decrease the toxicity of current IP chemotherapy regimens. A student on this project will focus on designing and prototyping 3D geometries for the implant as well as subsequent mechanical testing and data analysis.  An ideal student will be enthusiastic about learning techniques in device design, interested in expanding their general knowledge about translation biomedical devices, and committed to making an impact on the project.

Prerequisites: No experience is required. Prior knowledge of SolidWorks is preferred. Training will be provided in all areas. We will give preference to candidates who can commit to working at least 12 hours per week during the academic year. We are offering academic credit for new UROPs. The position is available starting September 2018.

Contact: Kriti Subramanyam (kriti@mit.edu)


9/20/18

Term: Fall/IAP

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Kripa Varanasi

Project Title: Mineral Recovery from Waste Flows

Project Description: Surface water flows are often polluted with nutrients due to agricultural run-off. If these nutrients reach lakes and rivers, they promote over-growth of algae which may result in destruction of other species within the water. In this project, we are exploring methods to remove nutrients from water to re-use them as fertilizers while also reducing pollution.

This project is primarily lab-based, and will involve preparing water samples by dissolving inorganic salts, preparing and/or using engineered nanoparticles, taking periodic samples to test for pH, conductivity, and zeta potential; and using an optical microscope. You will be working closely with a graduate student for the first month, and become more independent afterward. Time commitment will be about 5-10 hours per week with flexible scheduling. You will have the option of staying involved with the project after the fall semester, if desired.

Prerequisites: Looking for UROPs who have taken at least one chemistry lab for basic familiarity with lab safety and procedures. No other experience is required. Preference will be given to applicants with a strong interest in the subject, ability to work independently, and desire to become involved enough in the project to earn authorship on resulting publications.

Relevant URL: varanasi.mit.edu

Contact: Samantha McBride (smcbride@mit.edu)


9/20/18

Term: Fall

UROP Department, Lab or Center: Chemical Engineering (Course 10)

MIT Faculty Supervisor Name: Klavs F. Jensen

Project Title: Synthesis and functionalization of metal nanoparticles with 3D-printed continuous stirred-tank reactors

Project Description: In recent years, microfluidic reactors have been proposed as alternatives to conventional flask reactors for chemical synthesis. Such reactor formats, which can operate in continuous (single stream) or segmented-flow (two-phased flow), allow for rapid and controllable thermal and mass transfer and thus define an ideal medium for chemical reactions. In comparison with capillary based and chip-based reactors, a continuous stirred-tank reactor configuration operating in the sub-milliliter scale offers greater flexibility because of active mixing of precursors, multiple and controlled additions of reagents, solid handling, while facilitating reactions with slower reaction kinetics (reaction time in the range of hours).

In addition, the homogeneous concentration and temperature profiles realized by strong agitation in each chamber result in nearly ideal CSTRs in series RTD profiles and accurate predictability of reaction conversions. The CSTR reactors will be 3D printed allowing for the fabrication of various stainless steel or copper/stainless steel reactor units with N number of chambers for various unit operations. The goal of this project is to develop a versatile end-to-end synthesis platform for producing polymer-coated functionalized metal nanoparticles.

Student Responsibilities: Familiarizing with wet chemical methods, conducting experiments with CSTR reactors (including metal nanoparticle synthesis, polymer functionalization and purification), conducting measurements for the evaluation of particles size using dynamic light-scattering and working with MATLAB.

Prerequisites: Basic chemistry and/or reaction engineering principles; lab experience preferred but not necessary; experience with Matlab is a plus.

Contact: Ioannis Lignos (ilignos@mit.edu)


9/20/18

Term: Fall

UROP Department, Lab or Center: Sloan School of Management (Course 15)

MIT Faculty Supervisor Name: Zen Chu

Project Title: Quantifying innovation impact through temporal and geographical trends in healthcare using data analytics

Project Description: MIT Hacking Medicine has run healthcare entrepreneurship events around the world over the past 6 years. The group has amassed data from over 150 events including healthcare hackathons and design thinking workshops. Collectively, this repository of data could reflect the state of healthcare in a specific region at a specific point in time.

We are looking for an undergraduate researcher to develop methods to analyze this data in the context of macro healthcare and entrepreneurship trends. This will be a valuable experience for data analysts interested in working together with senior healthcare professionals and learning more about the complex healthcare space.

An ideal student would be familiar with data analysis techniques data mining, natural language processing (NLP) methods, phrase mining and topic modeling techniques to apply them to this data set and ascertain trends/associations.

Prerequisites: Basic proficiency in data analysis and data mining, natural language processing (NLP) methods, phrase mining or topic modeling techniques is preferred. We will give preference to candidates who can commit to working at least 12 hours per week during the academic year. We are offering academic credit for new UROPs. The position is available starting immediately.

Contact: Khalil Ramadi (kramadi@mit.edu)


9/20/18

Term: Fall

UROP Department, Lab or Center: Sloan School of Management (Course 15)

MIT Faculty Supervisor Name: Zen Chu

Project Title: Tracking successful innovations in healthcare throughout the entrepreneurial ecosystem

Project Description: Healthcare hackathons and other early-stage innovation events can result in teams and projects that go on to be extremely successful. What determines a successful team and how can we track their journey from formation to exit?

We are looking for an undergraduate researcher to develop methods to (1) examine the paths of successful startups in healthcare and (2) enable reliable tracking of teams in upcoming hackathons. An ideal student would be familiar with databases and data mining techniques, enthusiastic about applying them to this exciting problem, and willing and eager to connect with local startups via email, phone, or in-person.

Prerequisites: Basic proficiency in databases. We will give preference to candidates who can commit to working at least 12 hours per week during the academic year. We are offering academic credit for new UROPs. The position is available starting immediately.

Contact: Khalil Ramadi (kramadi@mit.edu)


9/19/18

Term: Fall/IAP

UROP Department, Lab or Center: Biology (Course 7)

MIT Faculty Supervisor Name: David Housman

Project Title: Genetic modifiers of Huntington’s disease

Project Description: David Housman helped pioneer the discovery of the genetic marker for Huntington’s disease (HD). The Housman lab now studies how the rest of the human genome controls the age at which a patient with the Huntingtin mutation becomes symptomatic for the disease. We have identified other genetic markers that modify HD age of onset by using extensive resources of patient samples and clinical data collected over decades from the world’s largest HD family in Venezuela. We are now characterizing dysfunction of the proteins encoded by these genetic variants in HD patient samples and mice models. Further, we aim to discover the role of modifier variants in the pathology of the disease by genetic manipulation in mice models and patient-derived induced pluripotent stem cells differentiated into neurons. Understanding how these genetic variants alter the course of the disease will distinguish the molecular pathways that are most capable of modulating Huntington’s onset. By going from genetic to molecular insights, we hope to target these modifier pathways to develop protective therapies capable of slowing HD pathology.

The objective of this UROP will be to assist in all aspects in identifying and characterizing genetic modifiers of HD. This work will be closely guided by a post-doc and technician in addition to offering opportunity for a more independent project upon demonstration of research prowess. There is also opportunity for computational bioinformatics work with large genetic and next-generation sequencing datasets on a high performance computing cluster.

Prerequisites: Previous experience with molecular biology techniques is preferred. For optional computing work, programming experience and familiarity with Linux is preferred but not required. Commitment beyond one term is required (at least through IAP or ideally for the year).

Contact: Christopher Ng (cwng@mit.edu)


9/19/18

Term: Fall

UROP Department, Lab or Center: Comparative Media Studies (21 CMS)

MIT Faculty Supervisor Name: Federico Casalegno

Project Title: Research Assistant in Robotics and Physical Computing

Project Description: MIT Design Lab At MIT, the Design Lab exists within a context of broad-based technological innovation and builds upon the unique advantages offered by this setting. The Design Lab’s projects engage new technologies and their potential to enable fresh and highly effective solutions to problems of significant social, economic, and cultural importance. We are particularly interested in the emerging possibilities afforded by: new information technologies; new material, fabrication, and construction technologies; new ways of providing functionality at micro and nano scales; new techniques for engineering biological materials and structures.

Main Tasks: Candidates will design, build and test prototypes of autonomous robotic solutions, in particular drones and rovers. They will select the most advanced technologies available today (sensors, connectivity systems, power sources) in order to build working prototypes of robots for extreme environments. They will be responsible of all the phases of the prototype design and development, from technologies and components selection to the actual making and testing of the prototype. Candidates will also help to build reliable interfaces for the extrapolation and visualization of data coming from sensors. Main tasks will cover the following areas: robotic control and navigation, Sensor Interface Board design and development, interface programming, computer vision and machine learning, visual odometry. Candidates will work in a multidisciplinary environment and will collaborate with industrial, interface, and user experience designers.

Prerequisites: Candidates should have a strong computer science background, and have advanced knowledge of methods, tools and processes that allow the making and testing of working prototypes of autonomous drones and/or rovers. Candidates have experience in building working prototypes of self-navigating drones or rovers embedding sensors and transmitting data via WiFi or Bluetooth. Candidates have the ability to select the optimal technological solutions and components (e.g. sensors, motors, batteries) available on the market on the basis of specific technical needs. They also have experience in creating reliable interfaces collecting, transmitting, and visualizing data coming from sensors. Candidates have excellent technical knowledge, and are also able to collaborate with experts from other disciplines, in order to design, build and test robotic solutions. In addition to being creative and skilled, the right candidate is a team player, self-motivated and has a demonstrated ability to meet deadlines.

Expected Expertise

  • [Required] Software Prototyping Skills
  • • Programming knowledge in Python, C++, and Arduino
  • • Embedded design experience (Raspberry Pi + Linux)
  • • Basic Electronics (I²C & UART)
  • • Image processing libraries
  • • Using autopilot libraries and interfaces (Dronekit & Ardupilot)
  • • Knowledge in interconnectivity protocols such as WiFi (HTTP, TCP, websockets etc.) and Bluetooth
  • • PCB design [Optional]
  • • Drone experience (Calculations, Building and Calibrating)
  • • Experience using electrochemical sensors and gas sensors
  • • Following industrial standards in building support electronics for sensors
  • • PCB design using Eagle or other software
  • • 3D modeling

Relevant URL: design.mit.edu

Contact: Sara Colombo (scolombo@mit.edu)


9/19/18

Term: Fall/IAP

UROP Department, Lab or Center: Nuclear Science and Engineering (Course 22)

MIT Faculty Supervisor Name: Emilio Baglietto

Project Title: Fast and efficient representation of uncertainty in computational fluid dynamics (CFD) simulations

Project Description: The standard modeling of turbulence in computational fluid dynamics (CFD) simulations introduces significant error and uncertainty when compared to experimental or turbulence resolving simulation.  This project seeks to represent this uncertainty through the use of Gaussian Random Fields (GRF), whose parameters are inferred numerically with Markov Chain Monte Carlo or other techniques.  The student will work with a 5th year graduate PhD student to help refine the current uncertainty representation in terms of simplicity and efficiency.  This will enable fast uncertainty quantification for realistic Nuclear Reactor flow simulations. Potential areas of research include the simulation of non-stationary GRF represented by the Karhunen-Loeve Expansion and sampling with the Polynomial Chaos Expansion approach.

Prerequisites: The student is expected to have some mathematics background, and ideally some understanding of correlated multivariate Gaussian distributions and sampling algorithms.  No background with CFD or fluid dynamics is required.

Contact: Michael Acton (actonm@mit.edu)


9/18/18

Term: Fall

UROP Department, Lab or Center: Sloan School of Management (Course 15)

MIT Faculty Supervisor Name: Stuart Madnick

Project Title: Cybersecurity management in organizations

Project Description: Description: We have several projects for cybersecurity in organizations such as estimating and managing cyber risks, preventing phishing attacks, analyzing the perception of cybersecurity at organizations, among others. For these projects, we need several students to join us at Cybersecurity at MIT Sloan.

Learning opportunities: Overall, these projects can enhance your critical thinking, literature search, qualitative research, and data analysis skills. Selected candidate(s) are expected to join the projects immediately.

Qualifications: Required skills include attention to details, as well as excellent reading, writing, and communication skills. Familiarity with cybersecurity is a plus but not required. Priority goes to students with a background in management, social science, and computer science. Basic programming skills (Python, R, or Matlab) are only required for projects with extensive data analysis. We are particularly interested in working with motivated and organized students who are committed to doing research.

Contact: Please email Dr. Mohammad Jalali (‘MJ’) at jalali@mit.edu with your CV and days/hours availability, and feel free to ask any questions.

Relevant URL: (https://cams.mit.edu)


9/18/18

Term: Fall/IAP

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Hugh Herr

Project Title: Design & evaluation of a lower extremity robotic prosthesis

Project Description: At the Biomechatronics Group in the MIT Media Lab, we develop robotic prosthetic devices for people with lower extremity amputation. The design of these devices involves mechanical design, electronics design, programming, testing, and evaluation. We are looking for a motivated UROP student to assist with the design, programming, and evaluation of a prototype robotic ankle prosthesis, who would like to gain experience working in a multi-discipline research environment.

The UROP for this position will have the opportunity to:

  1. Modify embedded controller code to increase functionality of prosthesis
  2. Assist with human subject trials
  3. Process & analyze data collected during testing
  4. Design and manufacture components for prostheses

Please send your CV as well as a description of any experience/projects relevant to this position to emrogers@mit.edu.

Prerequisites:

  1. Prior experience programming in MATLAB.
  2. Prior experience programming in C.
  3. Prior experience using Solidworks.
  4. Commit to at least 10 hrs/week.
  5. Prior machine shop experience is a plus.
  6. Prior research experience is a plus.

Contact: Emily Rogers (emrogers@mit.edu)


9/18/18

Term: Fall/IAP

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Cullen Buie

Project Title: A microfluidic device for bioremediation and concentration of rare earth metals

Project Description: Rare Earth metals are extremely valuable elements that are used in many industries, including personal electronics and defense. Currently there are no U.S. sources of rare earth metals.  Some studies have shown that specific bacteria can uptake these elements by absorption onto their cell membrane.  Not only does this lead to removal of toxins from the environment, but provides a potential source of raw materials for these industries. In the Buie Lab, we have developed a novel microfluidic dielectrophoresis (DEP) device to "trap" cells based on their surface charge.

The goal of this project is to evaluate the use of DEP to purify bacteria that can scavenge these valuable elements from natural environments.

Prerequisites: Microfabrication and bacterial cell culture experience preferred but definitely not necessary.

Relevant URL: http://web.mit.edu/lemi/

Contact: Chris Vaiana (vaiana@mit.edu)


9/18/18

Term: Fall/IAP

UROP Department, Lab or Center: Civil and Environmental Engineering (Course 1)

MIT Faculty Supervisor Name: Desiree Plata

Project Title: Drinking water vulnerability in relation to oil and gas production

Project Description: This project entails quantifying organic chemical constituents in drinking water sources in the eastern United States, areas of which have been richly developed for oil and gas exploration over the past decade. The UROP will participate in the analysis of hundreds to thousands of drinking water samples collected during the preceding summer months, learning how to analyze aqueous samples for a broad distribution of compounds including methane, volatile organic compounds, and less volatile hydrophobic organic analytes via gas chromatography and a variety of sample preparation techniques. 

Overarching goals of the project are related to assessing, predicting, and preventing public and ecological health impacts associated with domestic energy extraction. Please note that large amounts of glassware will need to be cleaned to a high standard to preserve sample integrity and allow for further field sampling, and participants should be prepared to assist in those activities in addition to the engaging intellectual ones.

Multiple students desired.

Prerequisites: Basic chemistry and/or organic chemistry a major plus; careful and organized working habits are strongly desired due to the complexity of the analysis and number of samples being processed.

Contact: Desiree Plata (dplata@mit.edu)


9/18/18

Term: Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Pattie Maes

Project Title: NeverMind

Project Description: NeverMind is an interface and application designed to support human memory. We combine the memory palace memorization method with augmented reality technology to create a tool to help anyone memorize more effectively. Early experiments conducted with a prototype of NeverMind suggest that the long-term memory recall accuracy of sequences of items is nearly tripled compared to paper-based memorization tasks. With this project, we hope to make the memory palace method accessible to novices and demonstrate one way augmented reality can support learning.

Prerequisites: Course 6 or course 9 w/programming experience, Junior, Senior or MEng.

Relevant URL: http://groups.csail.mit.edu/genesis/papers/2017%20Oscar%20Rosello.pdf

Contact: Oscar Rosello (rosello@mit.edu)


9/18/18

Term: Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Pattie Maes

Project Title: HeartBit

Project Description: HeartBit is an interface designed for haptic heart rate biofeedback. A handheld heart beats alongside your own, mirroring the size, weight, and movement of a hidden internal organ, now external and tangible in real-time. HeartBit offers a medium for users to self-regulate in moments of stress, anxiety or exertion: Control your heart to control your breath and body—for relaxation, performance enhancement, or augmented self-awareness.

Prerequisites: Course 6 or course 9 w/programming experience, Junior, Senior or MEng.

Relevant URL: https://oscar-rosello.com/heartbit/

Contact: Oscar Rosello (rosello@mit.edu)


9/18/18

Term: Fall 2018

UROP Department: Broad Institute (BR)

MIT Faculty Supervisor Name: Eric Lander

Project Title: Targeting the drug-resistant state in cancer

Project Description: We have recently discovered a novel mechanism that is naturally occurring in many cancers that promotes a cell state that is resistant to chemotherapy in the form of proteasome function inhibition. Using chemical and genomics approaches we have revealed that this drug-resistant state exposes new vulnerabilities that can be targeted with a specific drug. 

This project will focus on elaborating on these findings. Exploring both the mechanistic aspect of the chemical and genetic targeting of our newly described cancer drug-resistant state and on expanding these findings across other cancer therapy drug-resistance paradigms. The project will include construction of tools that will enable genetic manipulation of cells using CRISPR technology. Chemical genomic approaches in tissue culture models and large data set analysis will also be used. Overall it is a great opportunity to participate in a mature project that explores an exciting question of drug-resistance in cancer using all the new technologies in cancer cell biology in a great environment of the cancer program at the Broad Institute.  

Prerequisites: Must have passion for research and curiosity to learn. Previous experience with molecular biology and/or Cell culture is preferred. Large dataset analysis experience is a plus. Preference for students that can commit for a year. The work will be conducted under the close supervision of a senior post-doc in a great scientific environment, as science is an exciting and fun endeavor, an enthusiastic and committed UROP would be the ideal fit.  

Relevant URL: 

Contact: Peter Tsvetkov (ptsvetko@broadinstitute.org)


9/17/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Mathias Kolle

Project Title: Holography for photonic device design

Project Description: This project is all about making holograms. We are currently investigating chemical systems, exposure techniques, and new applications for analog holograms (see https://en.wikipedia.org/wiki/Holography for an overview and https://www.youtube.com/watch?v=WWV5gM9yNC0 for an example). You would be involved in making holographic plates from scratch and exploring different optical setups for exposing the plates to a laser. You would have a chance to make holographic images of anything you wanted, as well as taking some of them home. This is a good chance to obtain some hands-on experience with chemistry and and using lasers.

Prerequisites: Skills - basic optics, basic chemistry

Contact: Ben Miller (bmill@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Mathias Kolle

Project Title: Thermal actuation of complex liquid colloids

Project Description: This project involves conducting optical bench experiments using an infrared laser to manipulate emulsion-based bi-phase liquid colloids. These bi-phase emulsion droplets are comprised of two immiscible oils in a aqueous medium and display a variety of interesting physical properties including lensing, structural color, chemical responsiveness.  One attribute is how they respond to thermal gradients; the droplets will orient such that they will face towards a heat source.  In this project, the UROP will learn to fabricate bi-phase droplets and conduct experiments on an optical table using an infrared laser (Laser Safety training will be required). Optionally, we could also offer a project focussed on the construction of a temperature control stage as part of this project.

Prerequisites: No prior optics or chemistry experience is necessary. If interested in designing a temperature control stage, knowledge in electronics might be beneficial.

Contact: Sara Nagelberg (snnagel@mit.edu)


9/17/18

Term: Fall/IAP

UROP Department, Lab or Center: MIT Quest for Intelligence (QI)

MIT Faculty Supervisor Name: Aude Oliva7

Project Title: Large Scale Video Understanding and Memorability Project Description: What makes a video segment memorable? Our goal is to develop a quantitative measure of memorability for videos and then conduct user studies to gather memorability scores for hundreds of thousands of video clips to aid with large-scale video understanding and simultaneously improve our understanding of human memory. We are looking for students to help design and implement online, crowdsourced experiments that can be run at scale. We are looking for people who have experience with front-end programming (JavaScript).

Prerequisites:

  • Required: proficiency with python, javascript, html, jquery.
  • Recommended: 6.148, 6.170 or similar.
  • Bonus: 6.036, 6.819, or similar; familiarity with Amazon's Mechanical Turk is a plus.

Relevant URL: http://moments.csail.mit.edu/

Contact: Zoya Bylinskii (zoya@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Sanjay E. Sarma

Project Title: Designing a low cost wireless switch to apply voltage stimulus to responsive material

Project Description: The objective of this project is to design a prototype of RFID-based actuator to control responsive material. Tracking with passive RFID tags is inexpensive and is being used in various industry since the past two decades. One of the ongoing projects in our group is to build sensing/actuating capabilities onto these passive RFID tags. There are  responsive materials currently available which exhibit different optical/electrical/magnetic properties depending on the electric potential applied across the material. We hope to build a prototype of RFID-based actuator to control one such material. Integration of low cost wireless switch and responsive material enables us to create tags that show visual cues when selected by a reader.

The potential UROP student would understand how the RFID system works and design a deployable prototype. The work plan can be summarized in following steps:

  1. Understand the current prototype and the problem being addressed.
  2. Create a concept design incorporating the complete need requirements
  3. Build and test a prototype
  4. Improve the form factor to make it more adaptable (for example, possibility of attaching indoors as a part of IoT hardware at homes or warehouses)

Student will also interact with graduate students and research scientists, and can eventually get involved in other similar projects, if interested. If you are interested in getting hands-on experience in product design relevant to wireless sensing and actuation, this would be a great learning opportunity.

Prerequisites: UROP student is expected to have interest in Electronics prototyping, Mechanical design, and 3D printing.

Contact: Nithin Reddy K (nithin@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Materials Science and Engineering (Course 3)

MIT Faculty Supervisor Name: Krystyn Van Vliet

Project Title: Engineering in vitro tools for myelinogenic drug discovery

Project Description: Oligodendrocyte progenitor cells (OPCs) are a class of multipotent cells that, when differentiated properly, engage and enclose neuronal axons with a myelin sheath. Poor remyelination, due to hindered OPC migration, axon engagement, or differentiation, is associated with poor nervous system function in diseases such as multiple sclerosis. Understanding causes and potential treatments of disorders characterized by incomplete myelin production or myelin degeneration are particularly challenging due to a lack of preclinical, in vitro tools that replicate key aspects of the OPC-neuron interactions. Emerging research including our own suggests that mechanosensitivity of the oligodendrocyte lineage, and physical and mechanical characteristics of axons, may impact key features of myelination such as the onset of oligodendrocyte differentiation, thickness and length of the myelin segments. This project is part of a collaborative effort to engineer pre-clinical models of human myelination that are more predictive of

clinical outcomes, using a combination of materials engineering, high resolution 3D microfabrication, and human induced pluripotency technology.

The students will work closely with a senior graduate student and research scientist in the lab, and interact with several collaborators within MIT and external institutions to achieve common goals. He or she will have the opportunity to contribute to several aspects of this project, and become familiarized with an array of hands-on experimental techniques ranging from material design, processing and characterization, 3D printing, several microscopy modalities, and mammalian cell culture.

Prerequisites: The position will require regular maintenance of cells, as well as fabrication of various types of cell culture substrata. Some wet-lab experience is preferred but not required, as well as interest in the interface of materials and biological research.

Relevant URL: https://www.nature.com/articles/s41598-017-18744-6

Contact Name: Daniela Espinosa-Hoyos (ehoyos@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: AH Slocum (PI), NC Hanumara

Project Title: Precision dispenser for liquid medication to prevent overdose in children

Project Description: The objective of this project is to redesign and prototype liquid medication dispenser to achieve a better form factor and fit the existing liquid medication packages.

Students will have access to a high resolution and industrial scale 3D printer for iterating prototypes. The current design is at an intermediate stage and the UROP is ideally expected to first understand the functionality of the product and redesign it to be more effective in terms of size, stability when attached to the medicine bottle, re-usability, final packaging, leakages, etc. Student will work with the graduate students and can eventually get involved in user testing of the product with patients or caregivers.

If you are interested in getting hands-on experience in product design of a healthcare product, this would be a great learning opportunity.

Prerequisites:  Please only apply if you have very strong interest and skills in Solidworks, Intuitive Design, Product Design, 3D printing, and Hardware prototyping. Knowledge of Arduino (working with LCD, Timer and Bluetooth) is a plus.

Contact: Nevan Hanumara (hanumara@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: BCS, Computational Psycholinguistics Lab

MIT Faculty Supervisor: Roger Levy

Project Title: Eye tracking for language processing

Project Description: We are launching an exiting new project which uses eye tracking technology to study how humans read and process language in real time.  We are looking for a motivated student who is interested in language to join the project during the Fall semester. As part of the UROP, you will learn about experimental techniques in psycholinguistics and will be trained to operate a state-of-the-art eyetracker.  You will prepare materials for an eye tracking experiment and will contribute to the data collection process. Additionally, there will be an opportunity to participate in analyzing the collected data.

Prerequisites

  • Responsible, independent, and highly attentive to detail.
  • Ideally at least one semester of programming experience (e.g. 6.00/6.0001+6.0002).

Please include a CV and a copy of your transcript with your application.

Contact: Yevgeni Berzak (berzak@mit.edu)


9/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Chemical Engineering (Course 10)

MIT Faculty Supervisor Name: Michael Strano

Project Title: Production, processing, and manipulation of the 2D nanomaterials for biological and energy applications 

Project Description: Graphene and other nanosheets are a new class of atomically-thin nanomaterials that have attracted extensive attention in scientific society over last ten years. The first member of this material family, graphene, was first produced in 2005 and brought the 2010 physics Nobel Prize to the researchers who made the discovery. Since 2010, an explosive effort has been dedicated to exploit their extraordinary electrical, mechanical, optical, thermal, and chemical properties for applications ranging from electronics and supercapacitors to drug delivery and structural composites. In Strano’s lab at MIT, we study these materials for their potential application in biosensors and chemical sensors, electronic devices, and energy applications. Production, processing, and manipulation of these materials for these applications is a challenging task due to their common features such as hydrophilicity, anisotropy, polydispersity, etc. We have been developing a platform for controlled synthesis of these materials that will allow us to tune the electrical, chemical, optical, thermal, and mechanical properties of these materials and make them application-friendly.

As a student, you’ll be interacting with graduate students and postdocs in a multidisciplinary research atmosphere to learn about the synthesis and production of this class of materials, characterization using numerous spectroscopic and microscopy techniques, and altering their structure or refining them based on the application in mind. Some of the applications currently being investigated in Stano’s lab include preparation of these materials for nanotoxicity studies, size sorting and refinement of their surface chemistry, preparation of novel fluorescent biosensors, and developing photocatalysts for the CO2 capture and conversion.

Having some background in materials characterization methods and simple chemical synthesis, and also working with MATLAB is a bonus.

Prerequisites: Students with plan for year-long or longer research commitment with interest in biology, chemistry, bioengineering, or nanomaterials.

Relevant URL: srg.mit.edu

Contact: Dorsa Parviz (dparviz@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Computer Science and Artificial Intelligence Laboratory (CSAIL)

MIT Faculty Supervisor Name: Christopher Cassa

Project Title: Improving computational predictions of the impact of genetic variants

Project Description: The interpretation of variants in clinically actionable disease genes is becoming increasingly common, even in healthy individuals. There is now a set of 59 genes that are so clinically important that they are being checked for mutations, regardless of a patient’s clinical history. These genes are responsible for a variety of clinical syndromes and have been extensively studied. However, even in these well-studied disease genes, the majority of variants are only observed in one or two families. which makes it challenging to know whether they cause disease.

In this project, we will develop new data that can be leveraged in the clinical assessment of variants including novel predictions of structural consequences. We will use an established software approach to infer protein structures using evolutionary history, and make structural predictions throughout these 59 genes. Finally, we will develop a statistical or machine learning prediction framework that integrates the full set of variant observations and characteristics to improve predictions of clinical risk for individual variants, and prospectively measure its performance in a clinical diagnostic laboratory.

This project does not require any previous genetics or protein structure experience, but it would be helpful to have some Python and shell experience.

Prerequisites: Comfort with Python and bash shell would be very helpful, but neither is strictly required. Experience in genetics/genomics/protein chemistry would be great, but is not required.

Contact: Christopher Cassa (cassa@mit.edu)


9/17/18

Term: Fall/IAP

UROP Department, Lab or Center: MIT Quest for Intelligence (QI)

MIT Faculty Supervisor Name: Dr. Una-May O'Reilly

Project Title: Analyzing how humans make programming errors across languages

Project Description: Understanding how we write computer programs, a complex cognitive task, remains an open question. One way to gain an insight into this process is to understand how we make mistakes; how we start with an idea and oftentimes fail to appreciate and follow the semantics demanded by a programming language, resulting in bugs which we inadvertently introduce.

In this work, we want to explore mistakes of a similar nature made across different programming languages. For instance, we want to understand how programmers inadvertently introduce race conditions in different programming languages like Python or Java.

We want to perform a systematic study of what some of these errors are and how they manifest themselves in public code repositories. Such a study will help us build interpretable statistical models to recreate, predict, and possibly prevent programmers from committing them, irrespective of the programming language they write in. Such interpretable models will eventually help us understand gaps that exist in programmers' understanding of concepts, which lead to such errors.

This work will introduce UROPs to doing exploratory science, engineer systems, learn and use open-source tools, and rigorously analyze data.

Prerequisites: Any/all of 6.033, 6.035, 6.036. Write to alfa-apply at csail.mit.edu with your CV and mention relevant courses you have taken and your grades in them.

Relevant URL: http://alfagroup.csail.mit.edu/

Contact: Nicole Hoffman (alfa-apply@csail.mit.edu)


9/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Chemical Engineering (Course 10)

MIT Faculty Supervisor Name: Patrick S. Doyle

Project Title: Self-entanglement of circular chains

Project Description: Our everyday experience teaches us that a linear chain tends to become knotted when agitated (e.g. earphones stuffed into a pocket). Knot formation occurs when a chain end passes through a loop on the same chain and gives rise to an entanglement. What, then, happens with a circular chain with no chain ends? The lack of free ends leads us to intuit that circular chains cannot become entangled. However, recent studies have found that circular chains can indeed form entanglements, albeit via a different mechanism from linear chains. The way in which circular chains form entanglements is not well understood by the polymer physics community. We would like to perform experiments with jostled circular beaded chains to investigate this mechanism.

Contact: Beatrice Soh (bsoh@mit.edu)


9/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Aeronautics and Astronautics (Course 16)

MIT Faculty Supervisor Name: Afreen Siddiqi

Project Title: Distributed CubeSats Missions Cost and Risk Modeling

Project Description: Distributed Spacecraft Missions (DSMs) and satellite constellation missions offer unique advantages to Earth Observing scientists, including improved performance for key global coverage metrics over monolithic spacecraft, but also present key challenges to system architects. NASA Goddard Space Flight Center (GSFC) is currently developing a software tool, the Tradespace Analysis Tool for Constellations (TAT-C), to conduct pre-Phase A tradespace explorations, and MIT’s Strategic Engineering Research Group (SERG) is working closely with the NASA GSFC team to provide the Cost and Risk modules for this tool. The undergraduate student selected to work on this project will have the opportunity to join weekly NASA teleconferences and contribute methodology that will be incorporated within the final software tool.

There is one UROP position currently available for the following research tasks:

  1. Creation of a database of cube satellites costs, including total costs and sub-system costs.
  2. Assistance in creation and validation of parametric cost models relevant for cube-satellite constellation missions.
  3. Assistance in modeling constellation operating costs and the differentiation between dedicated and temporary (or virtual) ground stations.
  4. Assistance in risk identification and modeling for cubesat constellation missions.

Prerequisites: MATLAB and/or Python proficiency; course work or experience relevant to satellite mission operations and design

Contact: Afreen Siddiqi (siddiqi@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Kamal Youcef-Toumi

Project Title: Energy Harvesting Mechanism and System Development

Project Description: Every day, about 20% of the clean water produced in the world is lost due to pipe leaks. Due to limitations in available technologies, most of the leaks are either not found, or found too late. Every year, there are 240,000 water pipe breaks in the US, and many of them cause sinkholes and other severe

damage to the infrastructure. Water utilities need methods for detecting and locating such leaks before they become big breaks, so that they can perform preventative maintenance. Effective ways can be sending robots into the network to perform detection task or implementing sensors along pipes to achieve real-time health monitoring and prognostics. The success of robot manipulation and wireless sensor networks somehow requires the widely-distributed energy supply, and it gradually becomes the main constraint in our system. Thus, we are going to develop a piezoelectrics or electromagnetics mechanism and system, that can harvest kinematics energy from flow and regulate the output for better consumption by robots and wireless sensor networks.

This project combines theoretical, simulational and experimental analysis. The UROP will perform CAD modeling, hydrodynamics simulation, electronics rectifier design, device design, experiments and data analysis. This project is a great opportunity for undergraduate students to explore work in mechatronics, design, electronics and hydrodynamics.

Expected hours are 10 per week. The candidate should be committed to the project and interested in working with energy harvesting. The nature of extensive work with electronics parts desires a background of electronics engineering, but it is not required.

To apply, please email Xiaotong Zhang (kevxt@mit.edu) your current resume.

Prerequisites:

  • Proficiency in Solidworks and MATLAB
  • Creativity in design
  • Backgrounds of hydrodynamics, and electronics engineering, or willingness to learn quickly

Contact: Xiaotong Zhang (kevxt@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Kamal Youcef-Toumi

Project Title: Robot Stability and Manufacturability Improvement

Project Description: Every day, about 20% of the clean water produced in the world is lost due to pipe leaks. Due to limitations in available technologies, most of the leaks are either not found, or found too late. Water utilities need methods for detecting and locating such leaks before they become big breaks, so that they can perform preventative maintenance. This is to save water and protect infrastructure. Effective ways can be sending robots into the network to perform detection task, which we have already developed and tested in several field tests. But we want to further improve the stability and standardize the manufacturing process of the robot.

The current system can be improved to be more manufacturable and more robust. The system is prone to damage when it makes tight turns in pipe bends, and it is difficult to make repairs.  We would like to optimize the design to be easier to debug, switch to more durable materials, and also make the structure of the robot more rational to function. Moreover, the electronics for the detection robot consists of multiple chips and more than 40 wires. The UROP will also work on integrate these chips into one PCB board while maintaining the same functions and similar dimensions. The UROP can also work on how to optimize the PCB layout for less space consumption.

Expected hours are 10 per week. The candidate should be committed to the project and interested in working with electronics or device design.

To apply, please email Xiaotong Zhang (kevxt@mit.edu) your current resume.

Prerequisites:

  • Proficiency in Solidworks
  • Knowledge of technologies for remote control
  • Manufacturing experience, especially 3d printing
  • Proficiency in PCB design and experience getting PCBs manufactured
  • Ability to solder complex circuits

Contact: Xiaotong Zhang (kevxt@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Kamal Youcef-Toumi

Project Title: In-pipe Leak Repair Robot

Project Description: The average city loses 20% of its drinking water supply due to leaks that are too small to detect with conventional methods, or pipe bursts that were not caught in time. MRL has developed a few iterations of soft robot that can successfully detect leaks. After detection of in-pipe leaks, another big problem facing the engineers is how to repair the leaks in time. Currently most repair jobs are done by digging out a huge area around the pipe section, finding the leak and replacing the entire pipe, which is costly and labor-intensive. The goal of this project is to develop a few robotic modules that can accomplish the repair task without shutting down normal water service. The modules will need to operate under high water-pressure and high water-flow condition.

The UROP will be involved in the design and manufacturing process. The UROP will perform CAD and FEA on robot design. The UROP will also work on how to stably control the hardware with the use of Microcontrollers or higher-level controllers. The UROP will implement control software for the robot. The UROP will also work with data from multiple sources, such as government water departments, water associations and robotics companies to study in-pipe conditions and challenges for an in-pipe robot. The UROP will also carry out rapid prototyping for numerous designs. This project is a great opportunity for undergraduate students to explore interest in robotics design, rapid manufacturing, controls and coding skills.

Expected hours are 10-15 per week. The candidate should be committed to the project and interested in working with robotics. The nature of work with successive iterations necessitates a responsible and organized approach, and attention to details.

To apply, please email Steven Y. Yeung (yyeung@mit.edu) your current resume and a short cover letter explaining your interest in the project.

Prerequisites:

  • Proficiency in CAD
  • At least one completed course in coding
  • Knowledge of Python, FEA, Labview, AUV, or willingness to learn quickly, is a plus

Contact: Steven Y. Yeung (yyeung@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Kamal Youcef-Toumi

Project Title: Graphical UI Design for Smart Water Pipe Networks

Project Description: Every day, the underground water distribution pipe systems of the world lose 20% of their clean water supply due to leaks. Many of those leaks are either not found, or found too late. Water utilities commonly use a combination of nightline and acoustic leak detection to find leaks, however these methods require high levels of manpower and may not be able to identify small leaks. This project investigates through simulation of a new, smart water-pipe system with more sensors and capabilities to detect and repair leaks.

The UROP will create a user interface to allow easy access and visualization of the MATLAB model. The interface may dynamically interact with the model, potentially allowing the user to select what variables they would like to see, or choose what pipe conditions they would like to simulate by allowing the user to place leaks or other pipe features. This project is a great opportunity for undergraduate students to gain experience interfacing with a system model, and to improve their coding skills.

Expected hours are 8-12 per week. The candidate should be committed to the project and interested in creating an engaging user interface. The nature of work with developing an interactive interface necessitates a responsible and self-driven approach, along with ability to set and follow through on deadlines.

To apply, please email Elizabeth Mittmann (emittman@mit.edu) your current resume and a short cover letter explaining your interest in the project.

Prerequisites:

  • Experience with designing user interfaces, or self-motivation to learn
  • Some sort of prior coding experience
  • Knowledge of Matlab, or willingness to learn quickly

Contact: Elizabeth Mittmann (emittman@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Kamal Youcef-Toumi

Project Title: Soft Robotic Sensors for Pipe Leak Detection

Project Description: The average city loses 20% of its drinking water supply due to leaks that are too small to detect with conventional methods, or pipe bursts that were not caught in time.  We are working on an autonomous soft robot that can locate these small leaks before they become catastrophic.  In order to do this, we are developing flexible sensors that can characterize the leaks, as well as obstacles such as pipe joints.

For this project, we will develop test stands to test different configurations of the sensors.  We will also characterize the sensors and develop new ones.  Eventually, we will test these sensors underwater with simulated leaks.  Knowledge of Solidworks or CAD environment is recommended, and experience with an Instron or other universal testing system is a plus. Expected hours are 8-10 per week.

To apply, please email Tyler Okamoto (tylero@mit.edu) your current resume and a short cover letter explaining your interest in the project.

Prerequisites: CAD proficiency

Contact: Tyler Okamoto (tylero@mit.edu)


9/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: John Gabrieli

Project Title: Neurocognitive Correlates of Student Development Study

Project Description: This project investigates how socioeconomics status (SES) impacts brain structure and function, cognition, and academic achievement using neuroimaging (fMRI) and neuropsychological testing in adolescents (7th & 8th grade). We are seeking a UROP to help with neuroimaging sessions, scoring of neuropsychological assessments, and participant recruitment for ~6-10 hours a week. Because we work with a school-aged population, assisting on evenings and weekends is required.

Please contact Rachel Romeo and Melissa Giebler (rromeo@mit.edu; mgiebler@mit.edu) with a brief description about why you are interested in this project and how much time you plan on dedicating.

Contact: Rachel Romeo (rromeo@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Economics (Course 14)

MIT Faculty Supervisor Name: Robert Townsend

Project Title: Exploring Local Economic Heterogeneity with Unique Panel Data

Project Description: A great opportunity to work with Prof. Townsend on a unique panel data spanning several decades and multiple household- and individual-levels interview modules. We observe noticeable variation in levels of economic activity across neighboring and otherwise similar villages in Thailand. Possible explanations range from environmental, such as resource endowments, to local institutions, to individual choices. Our 20-year panel data from Thailand villages gives us a unique opportunity to explore and analyze the relative importance of these various sources, as well as potential changes in their trends over time, and the resulting insights into economic development theory and policy.

RA responsibilities include organizing and analyzing the data. The emphasis is on in-depth empirical analysis that takes advantage of the time series structure of the data and its long span. The project is best suited for students interested in working with microeconomic data, and improving their data analysis and coding skills. The candidate should be committed to the project, and be organized and responsible in their work.

To apply, please email Prof. Townsend (rtownsen@mit.edu) your current resume and a short cover letter explaining your interest in the project.

Prerequisites:

  • Proficiency in Stata, MatLab, or R
  • Coursework in economics or statistics is helpful

Contact: Robert Townsend (rtownsen@mit.edu)


9/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Prof. Yang Shao-Horn

Project Title: Investigation of viability of novel lithium battery discharge chemistry

Project Description: Project will deal with probing the discharge process of a new possible lithium battery chemistry to assess its viability as a next generation lithium battery technology. This stage of the project deals with assembling cells, discharging them and then characterizing the reaction products.

Prerequisites: Student must be willing to stay full time during IAP. Experience working in a glove box an asset. As is experience with characterization techniques such as XRD, Raman and NMR.

Contact: Graham Leverick (leverick@mit.edu)


9/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Biology (Course 7)

MIT Faculty Supervisor Name: Omer Yilmaz

Project Title: Regulation of colon cancer stem cells

Project Description: Colorectal cancer is a major cause of cancer mortality. Stem cells in the intestine and colon initiate cancers, usually with loss of the tumor suppressor gene APC. Analogous stem cells in tumors may regulate cancer progression. In the lab, we are using tools such as 3D organoid cultures, genetically engineered mouse models, transplantation mouse models, and CRISPR/Cas9 gene editing to study the role of cancer stem cells in colorectal cancer. Please see our publications in Nature 2016 and Nature Biotechnology 2017.

Contact: Jatin Roper (jroper@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: MIT Quest for Intelligence (QI)

MIT Faculty Supervisor Name: Mathias Kolle

Project Title: Detection of insect growth and development using machine vision

Project Description: We are looking for an undergraduate researcher to develop vision and automation systems to track insect development. Our lab studies photonic materials that occur in nature, and seeks to understand how these materials form and behave. Insects offer particularly spectacular examples of multifunctional, structurally colored materials, and are amenable to study throughout their lifecycle. Our current work focuses on wing development during pupal stages, which requires raising, monitoring, surgery, imaging, and survival studies. Thus, we are constantly looking to improve the processes around these insect studies.

The objective of this UROP is to develop a system that detects and records changes in insect life stages: the target deliverable would be an automated system that records pupation time for each individual insect on a rolling basis. Further design of the “automated laboratory” would be welcomed and encouraged! This UROP could also possibly expand to other work including analysis of microscopic images and other aspects of organism development, such as image stabilization and autofocusing throughout transparent materials.

Prerequisites: Experience in automation, image analysis, and machine learning would be very useful, but not strictly required.

Contact: Anthony McDougal (mcdougal@mit.edu)


9/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Amos Winter

Project Title: Developing lifecycle cost model for solar-powered, low-pressure drip irrigation systems for the Middle East and North Africa

Project Description: Drip irrigation can substantially increase crop yields and reduce water consumption for small farmers in the Middle East and North Africa. If the cost of solar-powered drip irrigation systems can be reduced, small holder farmers in the MENA region and globally could gain access to this technology. One way to reduce the cost is to uniquely optimize each system in order to produce the lowest cost design. This project focuses on developing a database and lifecycle cost model for the system that will enable the optimization.

During the project you will: 

  • 1) Conduct field research to develop a location-based cost database
  • 2) Research and modify cost models from literature
  • 3) Develop a custom cost model to estimate the lifecycle costs of drip irrigation systems
  • 4) Integrate the model and database into a design optimization scheme

The work for the project could be used for a paper or thesis with an economics/global development focus, and there may be opportunities to travel to the field sites with the lab. We expect the work to take 10-12 hours/week. Please contact us if you’re interested!

Note: the lab is in the Mechanical Engineering department, but the project is economics-focused.

Prerequisites:

  • Economics background or interest in economics research
  • Interest in global development research
  • Experience with managing databases useful, but not required
  • Coding experience useful, but not required (MATLAB, Python, etc.)

Relevant URL: http://gear.mit.edu/projects/drip.html

Contact: Fiona Grant (fionag@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Sloan School of Management (Course 15)

MIT Faculty Supervisor Name: Thomas Kochan

Project Title: Analyzing smartphone patterns of worker voice and advocacy

Project Description: Since 2016, the “Workit” smartphone app (developed by OUR Walmart, an advocacy organization that aims to advance the rights and well-being of retail employees) has been using artificial intelligence to provide answers to Walmart employees about their workplace rights and other areas of concern relating to their employment. You will work directly with the back-end of the app, in a project that will involve i) extracting, ii) cleaning, and iii) analyzing the data.

The project will help to develop data extraction and cleaning skills in a real-world setting. Subsequent analysis of the data will offer an opportunity to develop applied econometric/data science skills, and will provide knowledge of and insight into labor organizing and worker voice in one of America’s largest employers.

Prerequisites: Knowledge and experience of Stata required; experience with PHP and SQL desired.

Contact: Thomas Kochan (tkochan@mit.edu)


9/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Research Lab for Electronics (RLE)

MIT Faculty Supervisor Name: Yang Shao-Horn, Jeremiah Johnson, Rafael Gomez Bombarelli

Project Title: Database Development for Machine Learning Analysis of Battery and Fuel Cell Polymer Electrolytes

Project Description: Polymer electrolytes offer immense opportunities to transform electrochemical energy storage technologies including batteries and fuel cells by increasing safety and reducing costs.  The wide use of polymers in these applications is limited largely by lower ion conductivity than liquid and solid ceramic electrolytes, low interfacial charge transfer kinetics and lack of chemical and electrochemical stability. Overcoming these limitations is of paramount importance, and we are presently applying a combined computational-experimental screening approach to accelerate fundamental research determining key parameters that govern polymer functionality. A portion of this approach utilizes machine learning techniques to intelligently screen large databases for the identification of structure-property relationships and to predict new polymer materials.

On this project you will have the opportunity to join a multidisciplinary team that includes experimental and computational expertise. This work will be focused on compiling and analyzing polymer electrolyte data for lithium ion batteries from a variety of sources. The development of this database is critical to the machine learning techniques we are using, and after the database has been constructed, you will have the opportunity to participate in the machine learning analysis of the collected data.

A UROP working with our group will:

  • Collect and analyze polymer electrolyte performance data from a variety of sources
  • Collaborate on work incorporating this data into computational and experimental study of polymer electrolyte materials
  • Participate in biweekly team discussions of research progress

Prerequisites: None.  Experience with machine learning and/or familiarity with battery or polymer materials is beneficial but not required. Fall funding deadline: Thursday, 9/21

Contact: Jeffrey Lopez (jlopez1@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Nuclear Science and Engineering (Course 22)

MIT Faculty Supervisor Name: Elisabeth Reynolds

Project Title: Work of the Future (WoF)

Project Description: The MIT Industrial Performance Center (IPC) is an interdisciplinary research center that engages in research on firms industries and technological change in the global economy and how their emergence and transformation impact society at large (http://ipc.mit.edu).

The MIT Work of the Future (WoF) initiative, an IPC flagship project announced last spring,  brings together knowledge of engineering and technology with expertise in the humanities and social sciences including economics, history, education, business, industrial organization, political science, sociology, anthropology and public policy to address three primary questions:

  • 1. How are emerging technologies transforming the nature of human work and the skills required to thrive in the digital economy?
  • 2. How can we shape technological innovation to complement and augment human potential?
  • 3. How can civic institutions—existing and new—act to ensure that the gains from emerging innovations contribute to equality of opportunity, social inclusion, and shared prosperity?

The UROP will help with research for WoF on key developments related to the changing nature of work, with a particular focus on skills, education and training. The UROP will help with developing literature reviews, conducting secondary research on various programs, policies as well as emerging technologies. The UROP will also help with preparation for meetings, presentations and related activities of the Work of the Future Task Force. She/he will be included in meetings of the Task Force and with other visitors to campus.

Prerequisites: Prerequisites include: The selected candidate will have strong analytical skills, a good work attitude, excellent writing and interpersonal skills and experience in data/graphics presentations.

Relevant URL: workofthefuture.mit.edu

Contact: Laura Guild (lguild@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Research Lab for Electronics (RLE)

MIT Faculty Supervisor Name: Jongyoon Han

Project Title: Electrochemical neuromodulation

Project Description: We are offering an opportunity to get involved in one of today’s most exciting fields: neuro-engineering. Although relatively new, the field of neuro-engineering is developing quickly in terms of both basic research and industrial product development. The Micro/nanofluidic and BioMEMS research group is designing a neural prosthetic device that could offer a superior therapeutic solution for debilitating neurological conditions such as chronic pain and epilepsy. As a part of this project, we plan to hire a motivated undergraduate student whose role would be to fabricate and test this device. Specific tasks will be decided on an individual basis. However, available options include: neuronal cell culturing, genetic manipulation, and electrode construction.

The Micro/nanofluidic and BioMEMS research group led by Prof. Jongyoon Han has a broad, multidisciplinary focus—we are involved in several high-impact fields, which, in addition to neuro-engineering, include cell sorting, bio-molecule detection, and desalination. Appointed in both the electrical and biological engineering departments, Prof. Han has previously taught classes such as 20.330J, 20.370J, 20.470J, 6.021, and 20.334. Our group is welcoming and supportive, and we have had success engaging a number of undergraduate researchers over the years.

The neuro-engineering project, currently led by PhD student Matthew Flavin, evolved from a proof of concept, published several years ago, for a new method of modulating neurons based on focal chemical modulation. Following that success, one of our focuses is constructing a practical device capable of chronic operation. For your role in this project, you will work closely with Matthew Flavin to construct such a device.

If you are interested in this position or would like more information, please send us an email.

Relevant URL: http://www.rle.mit.edu/micronano/

Contact: Matthew Flavin (mflavin@mit.edu)


9/17/18

Term: Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Canan Dagdeviren

Project Title: Multifunctional Miniaturized Neural Interfacing Tool

Project Description: Our body is an ocean of patterns that we have not yet properly decoded. Our lab, Conformable Decoders, works on translating these biological signals around us - especially from the human body - into energy and data that we can easily understand. We microfabricate the devices for energy harvesting and sensing in our very own cleanroom (YellowBox) at the Media Lab. In this project, the student will collaborate closely with the student advisor to fabricate tools needed to test the devices and conduct tests in the cleanroom.

Depending on your expertise and interest, tasks may include:

Literature review and summarization of neural probe implantation, clinical biomarkers associated with Parkinson’s Disease, as well as combinatorial therapies for neurodegenerative disorders. Fabrication of mf-MiNDS components and electrical testing and validation, in vitro infusion characterization etc. We are looking for one UROP.

Prerequisites: We would like students who are careful, methodical, organized, and motivated. Working in the cleanroom as an undergraduate is an amazing opportunity - you will appreciate it. Though not required, prior experience in a research laboratory is preferred.  Exposure to fabrication (laser cutter, CNC/manual mill, simple electronics, etc.) and any experience in working with mice is a plus.

Contact: Nikita Obidin (nikitaob@mit.edu)


9/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Electrical Engineering and Computer Science (Course 6)

MIT Faculty Supervisor Name: Richard Fletcher

Project Title: Advanced Android Development for Health Diagnostics

Project Description: Our group develops a variety of mobile technologies to diagnose disease and detects abnormalities.  Sample applications include:

  • (1) Cardiovascular disease diagnostics -- CVD is the leading cause of death worldwide.  We use the phone camera and other custom sensors to assess cardiovascular health
  • (2) Diabetes -- this chronic disease is becoming increasingly common all over the world, including developing countries. We are exploring some early detection methods that can be implemented on a mobile phone to enable early intervention.
  • (3) Assessment of Malnutrition -- Malnutrition interventions are impeded by a lack of accurate measurements.  we use computer vision algorithms to automate anthropometric measurements for babies and toddlers.

A sample of our projects can be seen on our web page: http://mobiletechnologylab.org/portfolio/

Using a combination of mobile phone app with clever sensing techniques, machine vision, machine learning algorithms, and little or no external hardware, it is possible to make important contributions to preventative health and public health services both in the US and developing countries. Our group has many strong clinical partners in the Boston area as well as with top hospitals in India and latin america for field testing our technologies and bringing innovations to the field. The tools we are creating shall provide decision support and feedback for health workers in the field.

Prerequisites: Since this field is very  interdisciplinary, we welcome students with all levels of skills and interest areas. We are particularly interested in students with one or more of the following skills: Computer Vision, signal processing, and machine learning. Software will be implemented on Android phones and tablets using the JAVA SDK, and in some cases, using the native C NDK as well.

We are looking for students with a programming background in Android and/or C++.  No biomedical background is necessary, but of course general interest in health or creating technology that helps people is useful. The student should be able to work independently, and attend weekly group meetings to check on progress.  At this time we are interviewing students who are interested in working this Fall term and will hopefully continue through the IAP and beyond. Pay or credit is available or UAP project consideration. Opportunities to travel to  developing countries (e.g. India) are possible.

Relevant URL: http://www.mobiletechnologylab.org/portfolio/

Contact: Richard Fletcher (fletcher@media.mit.edu)


9/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Dr. John Gabrieli

Project Title: Neural Basis of Comorbidity in Reading and Math Disorders

Project Description: The goal of this project is to examine the neural basis of commonly co-occurring disorders including math disorder, dyslexia, and ADHD. The Gabrieli lab is recruiting children in 3 rd -6th grades for both neuropsychological assessments and neuroimaging (functional magnetic resonance imaging, or fMRI). We are seeking a UROP to assist in neuroimaging sessions, participant recruitment, database management, scoring of standardized neuropsychological assessments, and potentially neuroimaging analysis. UROPs should be available for ~6 hours/week. Please contact Anila D’Mello and Dayna Wilmot (admello@mit.edu; dvwilmot@mit.edu) to state your interest!

Contact: Anila D'Mello (admello@mit.edu)


9/13/18

Fall

UROP Department, Lab or Center: MIT Lincoln Lab (LL)

MIT Faculty Supervisor Name: Prof. Jeff Shapiro

Description: Interested in UROPing at Lincoln Lab this academic year, check out the available opportunities in the PDF below.

Apply: Please submit your resume and unofficial transcript to our website at www.ll.mit.edu/careers.   Make sure you indicate the position number you are applying for.


9/13/18

Fall

UROP Department, Lab or Center: MIT Lincoln Lab (LL)

MIT Faculty Supervisor Name: Various Faculty

Description: This academic year MIT Lincoln Lab will be sponsoring approximately 40 UROP positions on-campus.  These positions are open to all students.  To see a complete list of the available UROPs please view the PDF below.


9/13/18

Fall

UROP Department, Lab or Center: Sloan School of Management (Course 15)

MIT Faculty Supervisor Name: Thomas Kochan

Project Title: Analyzing smartphone patterns of worker voice and advocacy

Project Description: Since 2016, the “Workit” smartphone app (developed by OUR Walmart, an advocacy organization that aims to advance the rights and well-being of retail employees) has been using artificial intelligence to provide answers to Walmart employees about their workplace rights and other areas of concern relating to their employment. You will work directly with the back-end of the app, in a project that will involve i) extracting, ii) cleaning, and iii) analyzing the data.

The project will help to develop data extraction and cleaning skills in a real-world setting. Subsequent analysis of the data will offer an opportunity to develop applied econometric/data science skills, and will provide knowledge of and insight into labor organizing and worker voice in one of America’s largest employers.

Prerequisites: Knowledge and experience of Stata required; experience with PHP and SQL desired.

Contact: Thomas Kochan: tkochan@mit.edu


9/13/18

Fall/IAP

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Dr. John Gabrieli

Project Title: Neural Basis of Comorbidity in Reading and Math Disorders

Project Description: The goal of this project is to examine the neural basis of commonly co-occurring disorders including math disorder, dyslexia, and ADHD. The Gabrieli lab is recruiting children in 3 rd -6th grades for both neuropsychological assessments and neuroimaging (functional magnetic resonance imaging, or fMRI). We are seeking a UROP to assist in neuroimaging sessions, participant recruitment, database management, scoring of standardized neuropsychological assessments, and potentially neuroimaging analysis. 

UROPs should be available for ~6 hours/week.

Contact: Please contact Anila D’Mello and Dayna Wilmot (admello@mit.edu; dvwilmot@mit.edu) to state your interest!


9/13/18

Fall/IAP

UROP Department, Lab or Center: Electrical Engineering and Computer Science (Course 6)

MIT Faculty Supervisor Name: Richard Fletcher

Project Title: Advanced Android Development for Health Diagnostics

Project Description: Our group develops a variety of mobile technologies to diagnose disease and detects abnormalities. Sample applications include:

  1. Cardiovascular disease diagnostics -- CVD is the leading cause of death worldwide.  We use the phone camera and other custom sensors to assess cardiovascular health
  2. Diabetes -- this chronic disease is becoming increasingly common all over the world, including developing countries. We are exploring some early detection methods that can be implemented on a mobile phone to enable early intervention.
  3. Assessment of Malnutrition -- Malnutrition interventions are impeded by a lack of accurate measurements.  we use computer vision algorithms to automate anthropometric measurements for babies and toddlers.

A sample of our projects can be seen on our web page: http://mobiletechnologylab.org/portfolio/.  Using a combination of mobile phone app with clever sensing techniques, machine vision, machine learning algorithms, and little or no external hardware, it is possible to make important contributions to preventative health and public health services both in the US and developing countries. Our group has many strong clinical partners in the Boston area as well as with top hospitals in India and latin america for field testing our technologies and bringing innovations to the field. The tools we are creating shall provide decision support and feedback for health workers in the field.

Prerequisites: Since this field is very  interdisciplinary, we welcome students with all levels of skills and interest areas. We are particularly interested in students with one or more of the following skills: Computer Vision, signal processing, and machine learning. Software will be implemented on Android phones and tablets using the JAVA SDK, and in some cases, using the native C NDK as well.  We are looking for students with a programming background in Android and/or C++.  No biomedical background is necessary, but of course general interest in health or creating technology that helps people is useful.   

The student should be able to work independently, and attend weekly group meetings to check on progress.  At this time we are interviewing students who are interested in working this Fall term and will hopefully continue through the IAP and beyond. Pay or credit is available or UAP project consideration.  Opportunities to travel to  developing countries (e.g. India) are possible.

Relevant URLs: http://www.mobiletechnologylab.org/portfolio/

Contact: Richard Fletcher: fletcher@media.mit.edu


9/13/18

Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Canan Dagdeviren

Project Title: Multifunctional Miniaturized Neural Interfacing Tool

Project Description: Our body is an ocean of patterns that we have not yet properly decoded. Our lab, Conformable Decoders, works on translating these biological signals around us - especially from the human body - into energy and data that we can easily understand. We microfabricate the devices for energy harvesting and sensing in our very own cleanroom (YellowBox) at the Media Lab. In this project, the student will collaborate closely with the student advisor to fabricate tools needed to test the devices and conduct tests in the cleanroom.

Depending on your expertise and interest, tasks may include:

  • Literature review and summarization of neural probe implantation, clinical biomarkers associated with Parkinson’s Disease, as well as combinatorial therapies for neurodegenerative disorders. 
  • Fabrication of mf-MiNDS components and electrical testing and validation, in vitro infusion characterization etc. 
  • We are looking for one UROP.

Prerequisites: We would like students who are careful, methodical, organized, and motivated. Working in the cleanroom as an undergraduate is an amazing opportunity - you will appreciate it. Though not required, prior experience in a research laboratory is preferred.  Exposure to fabrication (laser cutter, CNC/manual mill, simple electronics, etc.) and any experience in working with mice is a plus.

Contact: Nikita Obidin: nikitaob@mit.edu


9/13/18

Fall

UROP Department, Lab or Center: Research Lab for Electronics (RLE)

MIT Faculty Supervisor Name: Jongyoon Han

Project Title: Electrochemical neuromodulation

Project Description: We are offering an opportunity to get involved in one of today’s most exciting fields: neuro-engineering. Although relatively new, the field of neuro-engineering is developing quickly in terms of both basic research and industrial product development. The Micro/nanofluidic and BioMEMS research group is designing a neural prosthetic device that could offer a superior therapeutic solution for debilitating neurological conditions such as chronic pain and epilepsy. As a part of this project, we plan to hire a motivated undergraduate student whose role would be to fabricate and test this device. Specific tasks will be decided on an individual basis. However, available options include: neuronal cell culturing, genetic manipulation, and electrode construction.

The Micro/nanofluidic and BioMEMS research group led by Prof. Jongyoon Han has a broad, multidisciplinary focus—we are involved in several high-impact fields, which, in addition to neuro-engineering, include cell sorting, bio-molecule detection, and desalination. Appointed in both the electrical and biological engineering departments, Prof. Han has previously taught classes such as 20.330J, 20.370J, 20.470J, 6.021, and 20.334. Our group is welcoming and supportive, and we have had success engaging a number of undergraduate researchers over the years.

The neuro-engineering project, currently led by PhD student Matthew Flavin, evolved from a proof of concept, published several years ago, for a new method of modulating neurons based on focal chemical modulation. Following that success, one of our focuses is constructing a practical device capable of chronic operation. For your role in this project, you will work closely with Matthew Flavin to construct such a device.

If you are interested in this position or would like more information, please send us an email.

Relevant URLs: http://www.rle.mit.edu/micronano/

Contact: Matthew Flavin: mflavin@mit.edu


 

9/13/18

Fall

UROP Department, Lab or Center: Nuclear Science and Engineering (Course 22)

MIT Faculty Supervisor Name: Elisabeth Reynolds

Project Title: Work of the Future (WoF)

Project Description: The MIT Industrial Performance Center (IPC) is an interdisciplinary research center that engages in research on firms industries and technological change in the global economy and how their emergence and transformation impact society at large (http://ipc.mit.edu).

The MIT Work of the Future (WoF) initiative, an IPC flagship project announced last spring,  brings together knowledge of engineering and technology with expertise in the humanities and social sciences including economics, history, education, business, industrial organization, political science, sociology, anthropology and public policy to address three primary questions:

  1. How are emerging technologies transforming the nature of human work and the skills required to thrive in the digital economy?
  2. How can we shape technological innovation to complement and augment human potential?
  3. How can civic institutions—existing and new—act to ensure that the gains from emerging innovations contribute to equality of opportunity, social inclusion, and shared prosperity?

The UROP will help with research for WoF on key developments related to the changing nature of work, with a particular focus on skills, education and training.   The UROP will help with developing literature reviews, conducting secondary research on various programs, policies as well as emerging technologies. The UROP will also help with preparation for meetings, presentations and related activities of the Work of the Future Task Force. She/he will be included in meetings of the Task Force and with other visitors to campus.

Prerequisites: The selected candidate will have strong analytical skills, a good work attitude, excellent writing an interpersonal skills and experience in data/graphics presentations.

Relevant URLs: workofthefuture.mit.edu

Contact: Laura Guild: lguild@mit.edu


9/13/18

Fall/IAP

UROP Department, Lab or Center: Research Lab for Electronics (RLE)

MIT Faculty Supervisor Name: Yang Shao-Horn, Jeremiah Johnson, Rafael Gomez Bombarelli

Project Title: Database Development for Machine Learning Analysis of Battery and Fuel Cell Polymer Electrolytes

Project Description: Polymer electrolytes offer immense opportunities to transform electrochemical energy storage technologies including batteries and fuel cells by increasing safety and reducing costs.  The wide use of polymers in these applications is limited largely by lower ion conductivity than liquid and solid ceramic electrolytes, low interfacial charge transfer kinetics and lack of chemical and electrochemical stability. Overcoming these limitations is of paramount importance, and we are presently applying a combined computational-experimental screening approach to accelerate fundamental research determining key parameters that govern polymer functionality. A portion of this approach utilizes machine learning techniques to intelligently screen large databases for the identification of structure-property relationships and to predict new polymer materials.

On this project you will have the opportunity to join a multidisciplinary team that includes experimental and computational expertise. This work will be focused on compiling and analyzing polymer electrolyte data for lithium ion batteries from a variety of sources. The development of this database is critical to the machine learning techniques we are using, and after the database has been constructed, you will have the opportunity to participate in the machine learning analysis of the collected data.

A UROP working with our group will:

  • Collect and analyze polymer electrolyte performance data from a variety of sources
  • Collaborate on work incorporating this data into computational and experimental study of polymer electrolyte materials
  • Participate in biweekly team discussions of research progress

Prerequisites: None.  Experience with machine learning and/or familiarity with battery or polymer materials is beneficial but not required.

Fall funding deadline: Thursday, 9/21

Contact: Jeffrey Lopez: jlopez1@mit.edu


9/13/18

Term: Fall/IAP

Multiple Openings

UROP Department, Lab or Center: The MIT Energy Initiative (MITEI)

MIT Faculty Supervisor Name: Francis O'Sullivan

Project Title:  Big data and the electric power system

Project Overview: The transition to a low-carbon energy future requires advanced analytics and creative problem solving.  Put your skills to work with our team to make that future a reality.  How is the electric power system responding to changes in the availability of variable renewable energy (VRE)?  To what extent can flexible power storage solutions optimize plant- and system-level operation?  What implications does this have for the future of the electric power system, especially with regard to generator operation and power market design?  Our team at MITEI is using big data to find out.  

Our UROPs work alongside data scientists, engineers, and economists to generate insights on these issues.  We are looking for candidates interested in helping with five specific areas.  

Across all topics of this UROP, participants will:

  • Compile and manage repositories of relevant data
  • Document findings for current and future researchers in the low-carbon energy space
  • Participate in weekly team discussions of research progress

Prerequisites: The best candidate will possess data processing and coding experience (e.g., Python or R) and an interest in working with a team of chemical engineers, data scientists, and economists to study the nexus of energy and the environment.  Familiarity with the electric power system, and/or statistical methods will be beneficial but is not required.

When applying, please note your preferences for the topics described below:

Project #1:  Systems-level techno-economic assessment of the US energy system

Description: Help us to expand our group’s cutting-edge techno-economic energy system model.  As a member of the team, you will compile and analyze cost and emissions data on major energy conversion technologies and assist in building a model of emissions across a number of key pathways in the existing energy ecosystem. 

Contact: Emre Gencer egencer@mit.edu

______________

Project #2: Spatio-temporal analysis of renewables generation and electricity demand to support renewables integration studies

Description: Assist with an ongoing study of changes in the delivered cost of electricity in response to increasing penetration of VRE resources.  You will have the chance to analyze historical load patterns and corresponding (simulated) wind and solar generation data for various electricity markets in the US. As a key model component, we need to identify “representative” load, wind and solar generation patterns across regions that adequately capture the prevailing variability wind and solar output as well the correlation between the availability of these resources and electricity demand.

Contact: Dharik Mallapragada dharik@mit.edu

______________

Project #3: Understanding the emissions consequences of an evolving electric power system

Description: Over the course of this UROP, you will gain a detailed understanding of the EPA’s air quality monitoring programs and be responsible for comparing and validating power plant emissions reported by the EPA’s CEMS program and by alternative air quality monitoring resources.  You will ultimately synthesize your findings into a comprehensive report for MITEI’s ongoing systems analysis work.

Contact: Bentley Clinton (bclinton@mit.edu)

______________

Project #4: Exploring and optimizing electric power system operation and dispatch

Description: We are looking for a UROP to assist our team in conducting a detailed analysis of the composition of the existing power generation fleet.  Using a global data set of plant attributes and temporally detailed data on plant operation, we aim to assess observed variation in plant operation and dispatch patterns.  Some background or interest in learning about thermodynamics and power generation technologies will be a plus.

Contact: Emmanuel Kasseris kasseris@mit.edu

______________

Project #5: Investigating of the techno-economics of hybrid systems using gas-turbines and advanced energy storage technologies (with Apurba Sakti <sakti@mit.edu>)

Description: We are investigating the techno-economics of hybrid systems that employ gas-turbines together with advanced energy storage devices such as batteries.  Your responsibility as part of the team will be to report on the various business cases for advanced energy storage systems in the context of a low-carbon energy future.  We are particularly interested in the ways that energy storage systems can alleviate the need for rapid generator ramping and the system-wide consequences of these changes in unit-level operation.  

Specific skills for this task (preferred but not required):

  • Familiarity with processing modeling platforms like Aspen Plus or HYSYS
  • Web development experience (Django, PhP, web programming and database development)

Contact: Apurba Sakti sakti@mit.edu


9/12/18

Term: Fall

UROP Department, Lab or Center: Economics (Course 14)

MIT Faculty Supervisor Name: Robert Townsend

Project Title: Modeling the effects of weather fluctuations and climate change on farmers’ behavior

Project Description: Crops throughout the world are affected by weather shocks. These already substantial impacts will intensify as climate change exacerbates the extent of weather fluctuations. Yet, the interactions of crop development, farmer’s cultivation decisions, and weather are not straightforward. An effective private or policy response requires understanding of the mechanics of these interactions. We model the dynamics of weather-crop relationship and estimate its parameters using a unique detailed panel data.

The RA will perform data analysis; model and implement a method for measuring price fluctuations; and automate data simulation procedure. The RA will work with data from multiple sources, such as a multi-module panel household survey, local weather stations, and regional price records. Data work responsibilities include cleaning and organizing the data; carrying out statistical, regression, and graphical data analysis; examining the data for individual, temporal, and spatial trends; writing up the findings in a report. This project is a great opportunity for undergraduate students to explore work in applied economics, and to improve their data analysis and coding skills.

Expected hours are 10-15 per week. The candidate should be committed to the project and interested in working with microeconomic data. The nature of work with large datasets necessitates a responsible and organized approach, and attention to details.

To apply, please email Kamilya Tazhibayeva (kamilya@mit.edu) your current resume and a short cover letter explaining your interest in the project.

Prerequisites:

  • Proficiency in Stata
  • At least one completed course in statistics or econometrics
  • Knowledge of Python and/or R, or willingness to learn quickly, is a plus

Contact: Kamilya Tazhibayeva (kamilya@mit.edu)


9/12/18

Term: Fall/IAP

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Joseph Paradiso

Project Title: Cognitive Audio: Translating Auditory Memory to Audio Capture Technology

Project Description: When we form memories, not everything that we perceive is noticed; not everything that we notice is remembered. Humans are excellent at filtering and retaining only the most important parts of their experience--  what if our audio compression could behave the same way? To achieve this, we are studying the factors that make sounds "memorable", and building an auditory memorability model as a function of low-level audio saliency features *and* high-level cognitive features (such as affect, familiarity, and consensus in free-text labeling). We’ve created a custom audio dataset and crowd-sourced labels for the high-level features, and have additionally collected memorability data using a custom game interface (keyword.media.mit.edu/memory).

We're now getting into the most exciting area of this work, which entails analyzing the data to help gain a deep understanding of auditory memory from the ground up, form classification models to assess "memorability" of audio samples, and even generative models to manipulate audio within the space of memorability.  The UROP project will most likely entail:

  • * data exploration, analysis, and visualization from our growing database
  • * design and management of additional novel experiments and data collection
  • * model architecting and training
  • * contributing new datasets, experiments, and models to a publication

Prerequisites:

  • Required: Strong background in data science or machine learning
  • Preferred: Experience with signal processing or audio

Contact: David Ramsay / Ishwarya Ananthabhotla (resenv-audio@mit.edu)


9/12/18

Term:Fall/IAP

UROP Department, Lab or Center: Electrical Engineering and Computer Science

MIT Faculty Supervisor Name: Arnaud Grignard

Project Title: CityScope & GAMA: An Agent based approach for Urban Modelling

Project Description: MIT Media Lab City Science group (https://www.media.mit.edu/groups/city-science/overview/) is searching for a candidate to conduct research and development of CityScope project. Key topics include UI/UX, hardware prototyping, development and maintenance, advanced end-user visualization and computer graphics in the field of ‘city science’. CityScope is a slew of tangible and computational urban simulation platforms for collaborative decision making and for tackling complex urban problems. Key topics include software and hardware development, data visualization and computer graphics in the field of ‘city science’. The researcher will develop and apply technologies that enable augmented reality tangible user interfaces (TUIs) for various projects at MIT and around the world. While working hand in hand with other Media Lab Researchers, the researcher will design and deploy software and hardware systems for exhibit at the Lab.

Interactive Visualization

This project is part of the framework of the usage of complex and multi-scale models for decisions support with a high interactivity. CityScope is a support for a prospective reflexion where the human intervention in time and space is taken in account like any other dynamics. The complexity of existing analytical processes remains a major obstacle making data visualization task a complicated process for many scientists or one reserved for design specialists. Programming interfaces and intelligent systems have already establish themselves as the most fruitful paths in the field of information visualization. We are particularly interested in the study of interactive visual representations of heterogeneous data to reinforce human cognition. Assuming that agent-based models properly represent the complexity of a real system, we propose to use an approach based on the definition of an agent-based model to facilitate visual representation of simulation outputs and complex data. Our approach, called Agent-based Visualization (ABV), gives a methodology to design a visualization using an incremental, generative, and interactive approach.

Context

These concepts would ideally be implemented in the GAMA modelling and simulation platform (http://gama-platform.org/). The student will be asked to search in a systematic way, beyond interaction and visualisation techniques to generalise its empiric results to obtain a reusable technic in various domains. It will be implemented as an extension of the already existing platform GAMA on which model are already implemented.

Prerequisites:

  • Software development skills: OOP in Java, C, C++, JS or equivalent.
  • Complex System Simulation skills: Cellular Automat, Agent Based Modelling
  • 3d modeling and rendering, Adobe CS, GIS, three.js and other map-making tools.
  • Proven Github activity and proficiency in revision control.
  • Capable of working in a dynamic, multicultural and challenging environment.
  • Excellent teamwork and social skills.
  • Experience in development of database and server side.
  • Architecture, urban planning or other design background.

Relevant URL:

Contact: Arnaud Grignard (agrignard@media.mit.edu)


9/12/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Roger Levy

Project Title: Computational models of vague language

Project Description: The fact that humans communicate relatively effectively using language is remarkable. Natural languages are rife with underspecification and vagueness, posing serious computational challenges to both humans and machines. Take the word "tall", for instance. "Tall" is vague and context-dependent: A tall building is much taller than a tall man, and there's no specific point at which something becomes "tall". A standard linguistic analysis will tell you that the word "tall" means that the height of the object is greater than some threshold, but how should a rational language user set the threshold? In this project, we will investigate different theories of the influence of context on vague language use using formal, probabilistic models of language and test them using behavioral experiments on human participants. Comfort with programming will be important.  Familiarity with probabilistic programming (e.g., WebPPL) will be useful but not necessary.

Prerequisites:

  • One semester of programming experience (6.00 or equivalent)
  • Experience with web programming
  • Experience in probability, statistics, and/or machine learning (6.041B, 9.40, or equivalent) is desired

Contact: MH Tessler (tessler@mit.edu)


9/12/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Roger Levy

Project Title: Social mechanisms of cultural evolution

Project Description: Human cultural knowledge seems to accumulate modifications and incremental improvements over generations, which seems to separate the cultural evolution of human societies from that other animals (Tomasello, 1999). It is believed that the innovative and cultural prowess of human beings comes from our ability to learn from each other (Henrich, 2015).

In this project, we will investigate the role of different forms of knowledge transmission (e.g, different kinds of language use, physical demonstrations, …) on human cumulative cultural knowledge in multi-generational video game experiments run on the internet. Comfort with web-programming is important

(JS / HTML / CSS). Some server side web development will be used (node.js). Natural language processing techniques may be used to analyze the transcripts of written language used to communicate across generations. Data analysis and reports will be written up using R / Rmarkdown.

Prerequisites:

  • One semester of programming experience (6.00 or equivalent)
  • Experience with web programming with a server
  • Experience in probability, statistics, and/or machine learning (6.041B, 9.40, or equivalent) is desired

Contact: MH Tessler (tessler@mit.edu)


9/12/18

Term: Fall/IAP

UROP Department, Lab or Center: Sloan School of Management (Course 15)

MIT Faculty Supervisor Name: Alessandro Bonatti

Project Title: Standard-Setting Organizations

Project Description: Standard-Setting Organizations (SSOs) provide forums for the development and establishment of broad consensus on technological standards prior to their adoption. The main economic advantage of SSOs is to solve the potential coordination failures that arise under unfettered market competition: standardization saves duplication costs, stimulates specific investments by complementary products, and avoids the risk of a standards war.

A standardization process “by consensus” has been used to establish a multitude of voluntary standards. However, shared interest in establishing a standard to realize the benefits of network economies often conflicts with the vested interests of each participant. Overall, the combination of free-riding, distributional conflicts and consensus requirements makes reaching an agreement quite challenging. How do an SSO’s internal rules and procedures impact the final outcome of bargaining among firms with competing technologies? How do they help avoid standards wars?

Scope: This research project aims to connect bargaining theory, organization design, and data on patents and the technologies included therein. The UROP for this project will be responsible for: 

  • 1. Conducting a thorough review (under faculty guidance) of the rules, procedures, and clauses of several SSOs, and how they impact firms’ bargaining over technological standards. 
  • 2. Identifying (again under faculty guidance) several publicly available datasets on patents, trademarks, and technology standards. See, for example, the references in https://onlinelibrary.wiley.com/toc/15309134/2018/27/3 
  • 3. Extracting and documenting the information in these datasets that is relevant to bargaining procedures and outcomes. 

A successful UROP will have the option to extend this project into the spring. 

Funding Options: For credit or for pay ($15/hour). 

Prerequisites:

  • Creativity, initiative, and an independent research spirit; seeking alternative sources, expanding the research domains (both theoretical and applied) beyond the ones we discuss together.
  • Good organization and communication skills.
  • Basic skills with statistical software (e.g., Stata) to run descriptive analysis of the available data.
  • Some experience with LaTeX and BibTeX, as well as a background or interest in economics or strategy, are helpful but not required.

Relevant URL: http://www.mit.edu/~bonatti

Contact: Dagmar Trantinova (dagmar@mit.edu)


9/12/18

Term: Fall

UROP Department, Lab or Center: Urban Studies and Planning (Course 11)

MIT Faculty Supervisor Name: Ceasar McDowell

Project Title: AR/VR Data Visualizations for Social Change

Project Description: The Quasar lab is an unofficial “Hacked” lab at MIT crated by CMS graduate student and filmmaker Sultan Sharrief. It brings together the Film & Music Industry, Big Data, AR/VR technologies, and critical pedagogy to understand ways to develop cultural “catalyst prototypes” that could create long-term social change for marginalized youth.

As part of this UROP you will work with the team and visiting “Artists in Residence” who will share their works of art and help to shape the CTC tool prototyping.

Research Objectives

  • -Support the marketing and rollout of the interactive portal “themove.mit.edu”.
  • -Do Data research on macroeconomics of systematic injustice
  • -Do research on social trends and the capacity for research in the public sector
  • -Design AR/VR data visualization tools
  • -Work with community organizations and youth groups

Contact: Sultan Sharrief (sultan.sharrief@gmail.com)


9/12/18

Term: Fall/IAP

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Prof. Nicholas X. Fang

Project Title: Design and Monitor Phase Change Window for Saving Building Energy Consumption

Project Description: Smart modulation of solar irradiance through windows has the potential to reduce building energy consumption on the HVAC system. Temperature-responsive hydrogel is a promising material to modulate light transmittance by changing the scattering properties of the small hydrogel particles. In our lab we recently developed a new kind of thermochromic window based on hydrogel particles which can effectively regulate solar irradiance in both visible and NIR region. For the next step of this project, we are curious of how this material performs under realistic environmental condition for building energy saving. The primary goal is to quantify the potential energy saving by this smart phase change window, and quantify the effect of it on the indoor environment.

In this project, you would be involved in: (1) Hydrogel particle synthesis by radical polymerization process and smart window assembly. (2) Demo/test “room” design for evaluating energy saving; (3) Monitoring solar heat flux and other indoor environment parameter (temperature, humidity, etc.) with wireless sensors. (4) Quantifying energy saving by the hydrogel smart window. (5) Investigation of the effects of material properties (phase change temperature, responsiveness, optical properties, etc.) on the building energy saving.

Prerequisites: Though not required,  experience in wireless sensor, system design, data processing, analysis coding (Matlab, Python, etc.) and familiarity with the basic concept of radiative heat transfer are preferred. Student should be familiar in using machine shop tools.

Relevant URL: https://web.mit.edu/nanophotonics/

Contact: Xinhao Li (xinhaoli@mit.edu)


9/12/18

Term: Fall/IAP

UROP Department, Lab or Center: Brain and Cognitive Sciences / McGovern Institute

MIT Faculty Supervisor Name: Ann Graybiel

Project Title:  High density micro-invasive probes for monitoring spatiotemporal dynamics of dopamine neurochemicals and neural activity from deep brain structures

Project Description: Our lab has developed novel subcellular probes that are smaller than single neuron cell bodies. These are the smallest implantable chemical sensors ever developed. These probes have now enabled us to monitor the rapidly fluctuating dopamine neurotransmitters that regulate our mood, motivation, movement, and many other key behaviors over long time scales (> 1 year). We are now working on advancing these tools to monitor across a wide network of brain sites in the basal ganglia. This would allow unprecedented view of how many brain sites communicate with each other and within local circuits, chemically, to shape behaviors related to controlling mood and movement. 

The undergraduate will be involved in fabricating and designing new arrayed versions of these probes to sample chemical activity from a high density of brain sites, and to perform surgeries and implantation procedures to test neurochemical recording function in anesthetized rats with drug manipulations. Measuring dopamine neurochemical activity across the striatal brain circuits will allow us to better understand the chemical processes that become dysregulated in a number of neurological disorders, including, Parkinson’s disease, Huntington’s disease, severe anxiety, and major depressive disorders. These studies would be pivotal to improving pharmacological treatments in patients, and to develop better therapies to restore normal activities in these patients. 

This is a highly interdisciplinary project combining engineering, microfabrication, and neuroscience. Students will learn about novel microfabrication procedures, neurochemistry, electrical circuits, and neurosurgery. Students may also be involved with programming, computational analysis, and circuit design, depending on their experience, background, and interests. We are looking for passionate and highly motivated undergraduates who can commit at least 12 hours a week and for both Fall and Spring terms.

Contact: Helen Schwerdt (schwerdt@mit.edu)


9/12/18

Term:Fall

Department/Lab/Center: Media Lab

Faculty Supervisor: Alex `Sandy' Pentland

Project Title: Studying team dynamics in MIT Delta V accelerator program

Project Description: Over the last two decades, many new startup companies have been founded, tackling problems in various fields, such as health, biotech, fintech, and clean energy. Nonprofit and for-profit organizations created incubators and accelerator programs that help guide the founders of these companies in their first steps as entrepreneurs in exchange for equity. In this high-risk environment, the ability to predict the success and failure of an early stage company is critical for investors. Prior studies marked human and social capital as important factors determining the potential of a startup to succeed. However, very little is known about the effect that founders’ interpersonal relationships have on the success of their companies, and the effect of their relationships with other startups located in the same innovation space.

In this project, we will look into team dynamics and performance in the MIT accelerator program Delta V. In particular, we will use machine learning tools to investigate the difference between low performing teams and high performing teams based on their interaction patterns, and how social interaction affect the quality of peer-prediction.

Our dataset contains six weeks of high resolution data collected last summer using Rhythm Badges, wearable devices that collect data on face-to-face interaction and conversational patterns (http://www.rhythm.mit.edu/rhythm-badges/).

This project is an exciting opportunity for students who are research oriented, and are interested in data analysis, networks and behavioral data. The results of this study will include a paper in a leading journal, and as a UROP you may participate as co-author. This will be discussed on an ad-hoc basis depending on student’s interests, skills, and availability.

Skills you need to already have: Experience with Python and/or R is required, but more advanced knowledge of data science will be very helpful. Experience with Python Pandas is a plus.

Other prerequisites:

  • Responsible, independent, and highly attentive to details
  • Available to work at least 10 hours per week

Contact: Oren Lederman (orenled@media.mit.edu) with a short description of your background or resume.


9/11/18

Term : Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Nicholas Makris

Project Title: Computational Analysis of Musical Instruments

Project Description: Music has apparently always been a part of human culture.  Many unsolved puzzles exist about how and why certain significant musical instruments evolved, such as violins and guitars. These puzzles can potentially be solved now with modern acoustics and computational abilities.

The emphasis this semester will be on plucked stringed instruments and their evolution. Each project will involve the construction of a digital musical instrument such as a violin, cello, guitar or lute from museum drawings or CT scans. This first step will involve developing a 3-D structure. This will then be incorporated into a dynamical model which will be used to analyze the physical properties of the instrument.  Simultaneous experiments will also be conducted to test the computational findings.

Contact: Professor Nicholas Makris (makris@mit.edu)


9/11/18

Term: Fall/IAP

UROP Department, Lab or Center: Aeronautics and Astronautics (Course 16)

MIT Faculty Supervisor Name: Afreen Siddiqi

Project Title: Autonomous Driving Systems: Forecasting Demand and Technology Costs

Project Description: In autonomous driving (AD) systems in vehicles, the physical components (hardware and software) are rapidly undergoing technological development. Furthermore, future market demands and trends are unknown for autonomous vehicles. These uncertainties make the design and optimization problem for architecture of AD systems extremely challenging. The overall focus of this project is to develop a tool for analyzing trade-offs between AD architectures on cost, safety and performance measures, and to identify optimal platforms that can provide value over at least a decade or more. This project is being conducted in close collaboration with Hitachi Automotive Systems. The undergraduate student or students selected to work on this project will have the opportunity to contribute analysis and/or create software modules that will be used for guiding architecture selection of future AD systems. Furthermore, they will be able to join bi-weekly teleconferences and interact with AD engineers at Hitachi.

Two UROP positions are currently available:

  1. Development of a forecasting model for demand of autonomous driving systems in vehicles. The model will differentiate between levels of system autonomy and types of vehicles.
  2. Development of a lifecycle cost model for autonomous driving systems. The model will estimate research and development costs and manufacturing and production costs. Additionally, the model will estimate costs incurred for changing AD architectures.

Prerequisites: Experience with python and/or MATLAB. Familiarity with statistical analysis.

Contact: Afreen Siddiqi (siddiqi@mit.edu)


9/11/18

Term: Fall/IAP

UROP Department, Lab or Center: Sloan School of Management (Course 15)

MIT Faculty Supervisor Name: Sharmila Chatterjee

Project Title: Statistical/Econometric Modeling of the Impact of Sales and Marketing Alignment on Sales Performance

Project Description: This project is the statistical part of research of the impact of sales and marketing alignment on sales performance, via different organizational mechanisms. The student will organize the data; carry out preliminary statistical, regression, and graphical data analysis; examine the data for spatial trends; perform hierarchical linear modeling for 3 organizational levels; and share the findings. This project is a great opportunity for an undergraduate student, with advanced coursework in Statistics/Econometrics, to explore the applied statistics work in management science, and to improve their data analysis and coding skills.

For Credit or Pay. The student will report to the Faculty Supervisor.

Prerequisites: The work should be carried out in relevant statistical package (SPSS, R, or Stata). The ability to code is preferred. Though not essential, familiarity with HLM7 software package would be helpful. The perfect candidate should be a Junior/Senior undergraduate student, or a sophomore with advanced coursework in Statistics/Econometrics. The nature of work requires a responsible and organized student with careful approach and attention to details. The candidate should be committed to the project, responsible and thorough in his/her work, committed to the timeline agreed and communicate in a timely manner with the Faculty supervisor.

Relevant URL: http://mitsloan.mit.edu/faculty-and-research/faculty-directory/detail/?id=41346

Contact: Sharmila Chatterjee (schatterjee@mit.edu)


9/11/18

Term: Fall/IAP

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Professor Joseph Jacobson

Project Title: Scaling Science: Predicting Scientific Innovation from Large Scientific Graphs

Project Description: We are computing on large (hundreds of gigabytes to terabytes) scientific graphs to predict highly impactful innovations before they spread across the scientific ecosystem. In parallel, we are also using this information to more fully understand how diverse, balanced, and impact-optimal teams can be constructed, both for scientific research and for scientific startups/ventures.

Prerequisites: Excellent programming abilities, ability to commit regular and consistently to the project, highly motivated and independent are all critical. Experience with machine learning (especially NLP/topic modeling and/or GANs/generative models), graph theory, and/or portfolio theory a plus.

Contact: James Weis (jww@mit.edu)


9/11/18

Term: Fall/IAP

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Joseph Jacobson

Project Title: Breaking the limitations of search with deep learning

Project Description: Commonly used search engines such as Google can retrieve relevant entries with high speed and accuracy from spaces as big as 10^10 - the number of pages on the Internet. In this case, the relevant entry/reference is located between the petabytes of others stored on the many drives of the datacenter. Finding a perfect drug for a protein is similar to searching for a perfect key to a lock when both key and lock are flexible requires to search in larger spaces such as 10^100 - the space of possible drug-like molecules. Spaces like this cannot be hashed/searched by enumeration and/or stored on the disk. Reinforcement learning has recently been used to solve the game of chess with an estimated Shannon complexity of 10^120, and more recently the game of Go complexity of 10^360. A few months ago we have developed a machine vision technique for fast and accurate drug-protein flexible shape matching using convolutional neural networks. We are working on to redefine what is possible with the design of a perfect drug given a shape of a protein in space of moves of at least 10^800.

The work could result in a high-profile publication and/or could potentially spin off into a company. Joint work with Joseph Jacobson, Michael Bronstein, and Yoshua Bengio.

Prerequisites:

  • Completed one or more machine learning classes at MIT (or equivalent research experience)
  • Fluent with either TensorFlow or PyTorch
  • 15-20h/week (full time during IAP)
  • Could be continued into BS/MEng thesis project / Ph.D. application
  • Fall funding deadline: Sep 21st

Relevant URL: affinity.mit.edu

Contact: Joseph Jacobson (resumes@media.mit.edu)


9/11/18

Term: Fall/IAP

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Ellen Roche

Project Title: Soft Robotic Strategies to Mimic Physiological Vessel Characteristics and Medical Devices

Project Description: Seeking student with mechanical background to develop an artificial vessel or device with tunable mechanical characteristics. Soft robotic fabrication techniques will be explored to develop bench top models or devices for diseased vessels. The project is closely linked to clinical interest and provides opportunity to explore the interface of medical devices and human physiology.

Relevant URL: https://ttdd.mit.edu/

Contact: Markus Horvath (mhorvath@mit.edu)


9/11/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Ann M. Graybiel

Project Title: Develop CRISPR constructs for targeting genes of interest in brains of mouse models of neurodegenerative disease 

Project Description: Help us solve the mysteries of the brain using your molecular cloning skills! This is an ideal project for students interested in putting their molecular biology experience to work toward unraveling the brain mechanisms of neurodegenerative disease, particularly Huntington's disease. You will help us to develop and clone new CRISPR-based tools to target genes in the basal ganglia system of mice. We will design and clone constructs for packaging in viral vectors. These vectors will be delivered to brain systems, in particularly the striatum and dopaminergic systems in mice and evaluated by anatomical/histological, and behavioral evaluations. This project combines molecular biology skills, surgical skills, anatomical and behavioral genetic approaches. The student will be fully supervised and can work on a flexible time schedule. The ideal applicant for this UROP position will have experience with molecular cloning; prior experience with rodent work at MIT is a plus.

Ideally, we would like to find a UROP who could work at least 12 hours per week and would potentially be interested in working with us for longer than a year. 

In the Graybiel lab, our goal is to understand the functions of neurons in the striatum and other brain areas in simple behavioral tasks performed by rats and mice, typically involving learning. The striatum is a key part of the basal ganglia that receives input from midbrain dopamine neurons, cortex, and thalamus. It is thought to be centrally involved in procedural learning, habit formation, action selection, and movement disorders like Parkinson’s disease, Huntington’s disease, and dystonia, as well as addiction, depression, obsessive-compulsive disorder, Tourette syndrome, schizophrenia, and other disorders.

Prerequisites: Ideally, we would like to find a UROP who can work at least 12 hours per week. UROP projects are for credit; with increasing experience or in special cases, we will consider UROPs for pay.

Contact: Emily Hueske (ehanna@mit.edu) and Alexander Friedman, PhD (afried@mit.edu)


9/11/18

Term: Fall/IAP

UROP Department, Lab or Center: Electrical Engineering and Computer Science (Course 6)

MIT Faculty Supervisor Name: Tomaso Poggio

Project Title: Deep Learning: Biology, Theories and Computer Vision

Project Description: We explore a wide range of computer vision and deep learning projects such as image classification, object detection, image segmentation and biologically-plausible learning algorithms. In some projects, we also study theoretical aspects of deep learning.

Project 1: Backpropagation (BP) has been long criticized to be somewhat not biologically-plausible. However, there are variants of BP that are more implementable by the brain and at the same time perform comparably to BP. In recent experiments, we have promising results scaling them to more real-world tasks.

Students are encouraged to either:

  • 1. Try new variants of this class of algorithms.
  • 2. Propose and try other biologically-plausible learning algorithms for training neural networks.

Project 2: Deep learning has recently been very successful in many applications. However, our theoretical understanding of deep learning has lagged behind. In this project, student run simulations to verify predictions from our recent series of work on a few theoretical puzzles of deep learning.

References:

Project 3: In a series of recent work, we try to incorporate the knowledge of object into deep learning networks and proposed a class of models we call "object-oriented" deep networks.

Students are encouraged to either:

  • 1. Implement "object-oriented" deep networks with PyTorch/Tensorflow and test its performance on wider range of computer vision tasks
  • 2. Try new variants of this class of models.
  • 3. (Advanced) Accelerate "object-oriented" deep networks with customized NVIDIA CUDA code

Other opportunities: https://cbmm.mit.edu/about/job-opportunities/mit-urop-masters-students-undergrads-join-cbmm-engineering-intelligence-team

Prerequisites: Good at any of the following languages: Python, Matlab, C++ or C.

Relevant URL: https://cbmm.mit.edu/about/job-opportunities/mit-urop-masters-students-undergrads-join-cbmm-engineering-intelligence-team

Contact: Qianli Liao (LQL@mit.edu)


9/11/18

Term: Fall/IAP

UROP Department, Lab or Center: Political Science (Course 17)

MIT Faculty Supervisor Name: Volha Charnysh

Project Title: Economic and Political Legacies of WWII in Poland

Project Description: In the wake of WWII, Poland experienced perhaps the most dramatic demographic and territorial transformation in Europe. The country lost one third of its prewar population to deaths, emigration, and border changes, turning from one of the most ethnically diverse into one of the most homogeneous states in Europe. How did the devastation caused by WWII affect Poland’s subsequent economic and institutional development? Did the experience of German occupation and subsequent population transfers facilitate the imposition of Communist rule in the 1940s? Do the legacies of violence by German occupation forces still matter for contemporary attitudes and behavior?

Prof. Charnysh needs a research assistant fluent in Polish to help conduct research on these related research questions. Wellesley and MIT students are encouraged to apply.

The undergraduate researcher will:

  • Collect data on the experience of German occupation in Poland and on subsequent Communist rule from primary and secondary materials in Polish
  • Compile literature reviews
  • Assist in assembling quantitative datasets
  • Facilitate email communication with Polish academics, archives, and governmental agencies

Prerequisites:

  • Polish language skills (preference for native speakers)
  • Interest in social sciences (history, political science, economics, sociology)
  • Attention to detail
  • Organized and responsible
  • Strong communication and writing skills
  • GIS or German language skills are a plus, but not required

Please provide details on any prerequisites or skills required for this UROP

Contact: Volha Charnysh (charnysh@mit.edu)


9/11/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Michael Triantafyllou

Project Title: Underwater Ring Recovery

Project Description: Looking for a UROP to work with our Remote Explorer (REx4) autonomous surface vehicle. REx4 is based on the WAM-V platform and has successfully been used to win the RobotX 2014 competition. Currently, the REx4 vehicle is being used for multiple research projects, including environmental monitoring, long-term autonomy development, and the 2018 RobotX Competition. RobotX is a Worldwide Collegiate competition created to encourage the enhancement of Autonomous Ocean Vehicles. During this competition teams demonstrate their vehicles ability in a series of given tasks.

REx4 must recover rings suspended underwater in the competition field. Rings of various colors, sizes, and weights will be attached at varying depths underneath a marker buoy on the water’s surface. It will demonstrate completion of this task by recovering a ring to the surface platform and returning it to judges. UROP would need to build a mechanism to grab rings and program the AUV attached to REx4 to use the mechanism autonomously.

Prerequisites:

  • Proficient in C++
  • Proficient with machining
  • Comfortable with designing and building mechanisms

Relevant URL: http://oceanai.mit.edu/robotx/pmwiki/pmwiki.php?n=Main.UROP1

Contact: Paul Robinette (paulrobi@mit.edu)


9/11/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Michael Triantafyllou

Project Title: RobotX Competition Autonomous Ball Shooting

Project Description: Looking for a UROP to work with our Remote Explorer (REx4) autonomous surface vehicle. REx4 is based on the WAM-V platform and has successfully been used to win the RobotX 2014 competition. Currently, the REx4 vehicle is being used for multiple research projects, including environmental monitoring, long-term autonomy development, and the 2018 RobotX Competition. RobotX is a Worldwide Collegiate competition created to encourage the enhancement of Autonomous Ocean Vehicles. During this competition teams demonstrate their vehicles ability in a series of given tasks.

REx4 must recognize a marker and launch an object into one of two openings. UROP would need to build a launching mechanism that operates autonomously. The launching mechanism must be triggered by a visual sensor and must send a ball through a specified square.

Prerequisites:

  • Proficient in C++
  • Proficient in machining
  • Comfortable with design and building mechanisms

Relevant URL: http://oceanai.mit.edu/robotx/pmwiki/pmwiki.php?n=Main.UROP4

Contact Name: Paul Robinette (paulrobi@mit.edu)


9/11/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Henrik Schmidt

Project Title: Programming Sensing of Underwater Acoustic Beacons with a Hydrophone Array

Project Description: We are looking for a UROP to work with our Remote Explorer (REx4) autonomous surface vehicle. REx4 is based on the WAM-V platform and has successfully been used to win the RobotX 2014 competition. Currently, the REx4 vehicle is being used for multiple research projects, including environmental monitoring, long-term autonomy development, and the 2018 RobotX Competition. RobotX is a Worldwide Collegiate competition created to encourage the enhancement of Autonomous Ocean Vehicles. During this competition teams demonstrate their vehicles ability in a series of given tasks.

A hydrophone array must be integrated into the REx 4 platform to allow the vehicle to locate underwater acoustic beacons. Data then needs to be processed such that the vehicle and maneuver to and hold station above a beacon.

Prerequisites:

  • Proficiency in C++ programming
  • Basic understanding of underwater acoustics

Relevant URL: http://oceanai.mit.edu/robotx/pmwiki/pmwiki.php?n=Main.UROP3

Contact: Paul Robinette (paulrobi@mit.edu)


9/11/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Michael Triantafyllou

Project Title: Developing mechanical mechanisms to extend the capabilities of MIT’s REx 4 Unmanned Surface Vehicle

Project Description: We are looking for a UROP to work with our Remote Explorer (REx4) autonomous surface vehicle. REx4 is based on the WAM-V platform and has successfully been used to win the RobotX 2014 competition. Currently, the REx4 vehicle is being used for multiple research projects, including environmental monitoring, long-term autonomy development, and the 2018 RobotX Competition.

RobotX is a Worldwide Collegiate competition created to encourage the enhancement of Autonomous Ocean Vehicles. During this competition teams demonstrate their vehicles ability in a series of given tasks.

To improve the functionality of the REx4 Unmanned Surface Vehicle for its research tasks and for the RobotX competition, multiple mechanical mechanisms have to be designed and manufactured. Structures are needed for mounting new sensor equipment, antennas, and electronics. Attachments for battery fastening have to be innovatively redeveloped.

Prerequisites:

  • Experience in machining metals
  • Proficiency in CAD design

Relevant URL: http://oceanai.mit.edu/robotx/pmwiki/pmwiki.php?n=Main.UROP2

Contact: Paul Robinette (paulrobi@mit.edu)


9/11/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Henrik Schmidt

Project Title: Vision Sensing for ASV to See Colors, Shapes, and Obstacles

Project Description: We are looking for a UROP to work with our Remote Explorer (REx4) autonomous surface vehicle. REx4 is based on the WAM-V platform and has successfully been used to win the RobotX 2014 competition. Currently, the REx4 vehicle is being used for multiple research projects, including environmental monitoring, long-term autonomy development, and the 2018 RobotX Competition. RobotX is a Worldwide Collegiate competition created to encourage the enhancement of Autonomous Ocean Vehicles. During this competition teams demonstrate their vehicles ability in a series of given tasks.

REx4 has a camera to view surroundings. UROP would need to write programs that would take in camera data and be able to identify locations and types of objects, shapes, and colors.

Prerequisites:

  • Proficient in C++
  • Experience with vision sensing, especially the OpenCV library

Relevant URL: http://oceanai.mit.edu/robotx/pmwiki/pmwiki.php?n=Main.UROP6

Contact: Paul Robinette (paulrobi@mit.edu)


9/11/18

Term: Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Pattie Maes

Project Title: Thermal feedback for emotional regulation

Project Description: Temperature influences our perception and cognition both at a conscious and subconscious level. These effects are rooted in our bodily experiences and interactions with the environment, and even embedded as metaphors in our language. By learning how temperature affects us in different contexts, we can make use of that knowledge to create interventions that help us with personal growth.

This project seeks to apply thermal interfaces to assist with emotional and attention regulation. Stress and attention levels can be inferred using implicit user inputs such as electrodermal activity, heart rate variability, and relative facial temperature. This information can then be used to determine appropriate thermal feedback to implicitly modify the user's perception and aid with emotional and attention regulation in a minimally disruptive fashion.

We have a working prototype and have run a pilot study. We are looking for someone to create the next form factor version, design a better feedback experience, and run user studies.

Prerequisites:

Required:

  • Solid programming, product design+CAD, and digital fabrication skills.
  • Very important: experience running studies.

Big plus:

  • Cognitive or neuro background

Preferably: juniors, seniors, or MEngs

Relevant URL: https://www.media.mit.edu/projects/chill-out/overview/

Contact: Tomás Vega (tomasero@mit.edu)


9/11/18

Term: Fall/IAP

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Joe Paradiso

Project Title: Stylistic Audio Manipulation for Information Delivery

Project Description: In today's world, music consumption is ubiquitous -- we listen while we drive, exercise, and relax, but especially as we work.  Literature also shows that we know the music we listen to extremely well, suggesting that we might notice subtle changes or additions to our music as a function of our level of engagement with a parallel task.  What if we could capitalize on this to build a system that stylistically modifies your personal music collection in real-time to convey ordinary notifications -- text messages, facebook posts, or an important email from your professor? 

The SoundSignaling project in our group has focused on developing and evaluating a prototype version of this system, rooted heavily in offline audio processing algorithms.  We are now looking to translate this to a light-weight platform (web extension, streaming service plug-in, etc) for widespread evaluation and experimentation.  The UROP project will likely entail:

  • Musical creativity:  drawing inspiration from the existing prototype, the student will be designing genre specific music manipulation algorithms that require only online processing of audio
  • Signal processing/ machine learning: implementing these algorithms, first offline and then in an online system
  • Web development: we envision the beta version as a browser extension, though the final form factor is open for discussion
  • Helping to design and run crowd-sourced experiments, and contributing to a publication

Prerequisites:

  • Required: experience in some subset of signal processing, machine learning, and web development
  • Preferred: interest in music or experience as a musician, with an open mind and creative approach! 

Contact: Ishwarya Ananthabhotla (ishwarya@mit.edu)


9/11/18

Term: Fall/IAP

UROP Department, Lab or Center: MIT Kavli Institute for Astrophysics and Space Research (MKI)

MIT Faculty Supervisor Name: Prof. Rob Simcoe

Project Title: Imaging the Early Universe in 3D

Project Description: The Optical Telescopes and Instrumentation Group in the MIT-Kavli Institute for Astrophysics and Space Research seeks one or more UROP students to assist in building a new spectrometer for the Magellan Observatory in Las Campanas, Chile (prototype to be deployed in 2019).  This instrument obtains 3-dimensional images of the universe using a bundle of 2400 optical fibers in the focal plane of the 6.5-meter diameter telescope. It will be used to study the dynamics of how matter flows into and out of galaxies in the early universe, regulating the fuel supply of nascent stars.

The student will work with Kavli scientists and engineers to develop real-time instrument control software, built around python clients communicating with a c++ host server to drive mechanisms, collect instrument telemetry, and operate research-grade CCD cameras.

The project will run throughout the fall semester and IAP, and can lead to travel opportunities to Chile for commissioning observations in Spring 2019. Interested parties should send a CV, including relevant programming experience, to Prof. Rob Simcoe (simcoe@space.mit.edu).

Prerequisites: Candidates should have prior skill with python, as well as Linux-based c++ with an emphasis on object oriented programming and custom classes. Experience in GUI programming with Tkinter or other packages is helpful but not required, as is familiarity with TCP/IP-based client-server architecture and Raspberry Pi modules.

Relevant URL: http://ait.mit.edu

Contact: Rob Simcoe (simcoe@space.mit.edu)


9/11/18

Term: Fall

UROP Department, Lab or Center: Edgerton Center

MIT Faculty Supervisor Name: Diane Brancazio

Project Title: Develop Maker projects for K-12 core academic classes

Project Description: The Edgerton Center has a mission of developing and fostering experiential learning opportunities for K-12 students as well as MIT students.  In our Maker project initiative we help K-12 educators design and implement Maker projects in their core curricula. We define Maker projects as authentic (students have a personal interest in the project), project-based learning activities, that involve community and collaboration, and have a strong component of hands-on technology-based tools (think 3D printer, laser cutter, Arduino microcomputer, electronics, shop tools, sewing machine). We intend our methodology to be used by K-12 educators who seek to integrate STEM and Maker activities in core academic subjects, including Social Studies, English/Language Arts, Math, Science, and World Languages.

We are working with a group of K-12 schools to develop this methodology and sample projects.  Our need is for students to create project samples that will inspire the teachers in this group and show the range of opportunities available with the maker technologies.  We anticipate this being very creative and iterative, with students using tools and materials at our shop. They will design and create the kinds of projects they wish they could have done in high school or middle school, informed by the collaborating K-12 teachers.

Prerequisites: General familiarity with maker tools and materials. Experience with shop tools, digital fabrication tools, and 2D/3D modeling packages is preferred but not required.

Relevant URL: Information on our K12 Maker Projects initiative http://k12maker.mit.edu/k12-maker-projects.html

Contact: Diane Brancazio (dianeb@mit.edu)


9/11/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Nancy Kanwisher

Project Title: Neuroimaging studies of visual object processing

Project Description: Humans perceive objects quickly and effortlessly and they can continue processing them even when these objects are getting occluded. In this project, we would like to investigate the neural correlates of object processing under occlusion using magnetencephalography (MEG). This UROP includes the creation of dynamic stimuli using UNITY, experimental design and programming, and assisting in MEG data collection and analysis.

Prerequisites:

  • Experience with UNITY
  • Matlab programming skills

Relevant URL: Find out more about the Kanwisher lab: http://web.mit.edu/bcs/nklab/

Contact: Katharina Dobs (kdobs@mit.edu)


9/11/18

Term: Fall

UROP Department, Lab or Center: Research Lab for Electronics (RLE)

MIT Faculty Supervisor Name: Marin Soljacic

Project Title: Synthetic gauge fields in photonic Floquet systems

Project Description: The physics of a photonic structure is commonly described in terms of its apparent geometric dimensionality. One symmetry of a photonic structure is reciprocity---a fundamental principle in optics, requiring that the response of a transmission channel is symmetric when source and observation points are interchanged.

With the concept of synthetic dimension, it is in fact possible to explore physics in a space with a dimensionality that is higher as compared to the apparent geometrical dimensionality of the structures. One viable way to break reciprocity is via the synthetic dimension. Concretely, modulation-based T breaking was recognized long ago and revitalizes with much attention recently, under the context of Floquet topology.

This project is ideal for student interested in topological photonics and/or gaining lab experience. We will experimentally investigate photonic synthetic gauge fields in Floquet systems via T-breaking dynamic modulation. The UROP student will work with a senior graduate student on an experiment on this topic. Scientifically, the experiment aims at creating nontrivial topological phases. Application wise, the project may introduce new approach for topological quantum computation. Ideally, the student will come up with new theoretical and experimental possibilities as he/she gets familiar with the content of research.

References:

Prerequisites:

  • Require relatively flexible schedule as measurements may take several hours to a day.
  • Students with strong experimental capabilities are welcome to apply
  • Any major is welcome to apply
  • Familiarity with tabletop optics is welcome but not required
  • Familiarity with fiber optics, fiber optical devices is welcome but not required
  • Familiarity with digital signal processing is welcome but not required
  • Familiarity with gauge theory is welcome but not required

Contact: Yi Yang (yiy@mit.edu)


9/11/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Nancy Kanwisher

Project Title: Behavioral studies of human face perception

Project Description: How does human face perception unfold over time? Inspired by neural data, we would like to test the speed of processing different facial dimensions such gender, age or identity in humans. This UROP would involve the design and implementation of behavioral experiments, data collection and analysis.

Prerequisites: Matlab programming skills.

Relevant URL: Find out more about the Kanwisher lab: http://web.mit.edu/bcs/nklab/

Contact: Katharina Dobs (kdobs@mit.edu)


9/10/18

Fall 2018

Department/Lab/Center: Sloan School of Management

Faculty Supervisor: Daniel Greenwald

Project Title: Uncovering Firm Debt Covenants with Text Scraping and Analysis

Project Description: Corporate debt often contains restrictions, known as “covenants,” that can cause large penalties for firms that violate them. As a result, these covenants can have important effects on how firms react to economic conditions. For example, covenants that require a firm to stay below a maximum ratio of interest payments to earnings can cause sharp responses when interest rates rise, with potentially large economic consequences.

Despite the importance of these covenants, no comprehensive dataset exists detailing the covenants that apply to major firms in the US. However, this data is available in text form on the SEC’s portal “EDGAR.” In this project, student researchers will develop code to crawl EDGAR, extract the relevant text data, and develop and train algorithms to translate the text data into a usable catalog of covenants that can be used for novel economic research.

Project Details: The project will require 8-10 hours of work per week during the Fall semester, with opportunities for continued research available upon completion. The key prerequisite is knowledge of or willingness to learn Python.

Contact: Dan Greenwald, dlg@mit.edu


9/7/18

Term: Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Joe Paradiso

Project Title: Physical Interfaces for Deep Engagement

Project Description: We know that having your phone out on the table can lead to a significant decrease in cognitive capacity (Adrian Ward et al 2017).   This suggests that some aspect of our interaction with smartphones has fundamentally limited our ability to deeply focus on a task.

I'm interested in unpacking both (1) what aspects of the smartphone interaction design lead to this cognitive effect, and (2) in what ways do the 'attentional baggage' associated with a smartphone translate to *new* devices that might have similar affordances or similar functions.

Ultimately, the goal is to create design principles for physical interfaces that encourage focus, mastery, and deep engagement.  Do multifunction devices implicitly encourage divided attention?  Are there physical affordances (i.e., something in the shape of a phone, or something with a touchscreen) we should avoid or constrain?  How do we avoid designing devices that don't suffer from or perpetuate the smartphone cognitive load phenomena?

Relevant URL: https://www.journals.uchicago.edu/doi/pdf/10.1086/691462

Contact: David Ramsay (dramsay@mit.edu)


9/7/18

Term: Fall/IAP

UROP Department, Lab or Center: Aeronautics and Astronautics (Course 16)

MIT Faculty Supervisor Name: Alvar Saenz-Otero

Project Title: Zero Robotics: High School Tournament Game Programing

Project Description: Zero Robotics (http://zerorobotics.mit.edu/) is a programing competition which allows high-school students to program the SPHERES satellites (http://ssl.mit.edu/spheres). Student compete first in simulation, finalists compete in a live tournament run by astronauts aboard the International Space Station.

Zero Robotics has openings for up to 8 students to help us continue programing the current game for the Fall Tournament and to work on the next game that will use the new AstroBee Free flyer (https://www.nasa.gov/astrobee) for the 2019 competition.

Responsibilities will include:

Current 2018 High School competition on SPHERES:

  • * Programming and testing of the 3D game
  • * Balance game parameters in different phases of the tournament
  • * Maintain the "Leader Board"
  • * Assist the competitors

Game Development for the 2019 competition on Astrobee:

  • Develop an efficient pipeline for simulating student code on Astrobee
  • Create a highly engaging game that uses the new Astrobee architecture
  • Design a game with multiple winning strategies and a balanced set of 'obstacles'

Time: 6 to 12 units (can discuss credit or pay)

To apply:  Please submit resume to: zr-officers@mit.edu

Prerequisites: Previous programming experience in any language-highly desirable. Previous experience with robotics  competitions (ZR, FIRST, Roboball, etc) a plus.  All years welcome.

Relevant URL: http://zerorobotics.mit.edu

Contact: Alvar Saenz-Otero (zr-officers@mit.edu)


9/7/18

Term: Fall

UROP Department, Lab or Center: Economics (Course 14)

MIT Faculty Supervisor Name: Prof. Rob Townsend

Project Title: Building Healthcare Infrastructure in Indonesia

Project Description: The Indonesian healthcare system is unique in its speed of expansion over the last few decades. A multi-layered system of hospitals, clinics, and smaller facilities work in concert to provide access to even the most remote parts of the nation. Indonesia’s innovative approach of leveraging non-hospital facilities and non-physicians, including nurses and midwives, carries general insights for developing countries confronting rising healthcare needs under significant resource constraints. We study the expansion of Indonesia’s healthcare system and attempt to draw lessons on how best to allocate health services in limited-resource settings. To this end, we have compiled village-level data on healthcare infrastructure and health outcomes spanning two decades.

Scheduling is flexible, and work can be done remotely. The key task will involve compiling land price data in order to assess the cost of building new healthcare facilities. For each neighborhood, we will query real estate websites and record listings in the area. We will then use these listings to construct land prices. A more ambitious approach will use existing data on land prices in Jakarta to train a machine learning algorithm for predicting land prices across the country.

To apply, please email Allan Hsiao (ajhsiao@mit.edu) by Monday, September 17, 2018 with a current resume and a short cover letter explaining your interest in the project.

Prerequisites: Coding skills are required, and coursework in economics is helpful. The ideal candidate will have experience with data analysis, and will be highly organized and proactive. This project is best suited for students with interests in economic development, industrial organization, and healthcare.

Contact: Allan Hsiao (ajhsiao@mit.edu)


9/7/18

Term: Fall

UROP Department, Lab or Center: MIT Quest for Intelligence (QI)

MIT Faculty Supervisor Name: Yonina Eldar

Project Title: From data to diagnostics in ultrasound imaging

Project Description: Ultrasound imaging is one of the simplest medical imaging modalities. However, its quality is inferior compared with other modalities such as MRI and CT. Ultrasound systems today output an image which is formed by linearly combining reflected pulses from multiple received channels, referred to as channel data. The method of choice in all ultrasound systems to date is referred to as beamforming, and is based on well-known principles dating back decades ago. This process collapses the channel data to a single line in the image. In this project we intend to explore whether improved diagnostics can be performed by removing the beamforming step and processing the channel data directly using modern tools of deep learning. We expect to be able to improve the diagnostic ability of ultrasound by replacing the beamforming block by more modern tools and fully exploiting the information available in the multiple channel data.

Prerequisites: knowledge in deep learning

Contact Name: Yonina Eldar (yonina@mit.edu)


9/7/18

Term: Fall

UROP Department, Lab or Center: MIT Quest for Intelligence (QI)

MIT Faculty Supervisor Name: Yonina Eldar

Project Title: removing technician dependence in ultrasound

Project Description: Creating a good ultrasound image requires a skilled technician. The image quality is very dependent on the pressure and movement applied by the technician performing the scan. The goal of this project is to explore methods for removing the technician dependence by using deep learning and reinforcement learning techniques in order to automatically guide the technician as the image is being formed. This will enable wide spread use of ultrasound imaging without the need for a highly skilled technician which limits the applicability of this imaging modality.

Prerequisites: knowledge in machine learning

Contact: Yonina Eldar (yonina@mit.edu)


9/7/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Laura Schulz

Project Title: Human infants' understanding of basic physics: Web-based experiments for cognitive development

Project Description: The Lookit team is currently conducting the largest ever longitudinal study of infants (ages 4mo-1 year) and their expectations about basic physical principles like gravity and inertia. This project is also unique in developmental psychology because rather than bring families to the lab to participate in studies about cognitive development, we've developed a website where parents and children can participate from home at any time, with video of the child's responses recorded via webcam and sent to the lab for later analysis.

Our primary goals are (a) to accelerate robust, reproducible developmental science by reducing the practical barriers to conducting the “right” study to answer a particular scientific study, and (b) to expand participation in research to a more representative population of families.

This semester, we are looking for a UROP to annotate and analyze video data of our infant participants (75% of your time), and to take on additional projects as time and interest allows (25% of your time). Depending on your background and interests, this could include:

  • * Data analysis and visualization projects (especially for students interested in working in the lab for multiple semesters)
  • * Identifying and pursuing opportunities for local, online, and media outreach/recruitment (e.g., social media, family-oriented science events, online parenting), and/or writing content for blog posts
  • * Researching and expanding the Resources page of Lookit that connects families with in-lab research opportunities around the country and activities they can try at home

This UROP can be done for class credit, or you can apply for Direct Funding via the UROP office.

Prerequisites: The most important prerequisite for this position is that you be careful, thorough, and self-motivated - the quality of your work is critical for the success of this project!

A background in programming is not required, but will be helpful and will shape the kinds of projects you will take on in the lab. UROPS should be prepared to work with command line tools and create machine-readable data files. (If you come in without any programming background, you will work on gaining it!)

We will give preference to students who can commit to working for both the fall and spring.

Relevant URL: https://lookit.mit.edu/

Contact: Melissa Kline (mekline@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: MIT Quest for Intelligence (QI)

MIT Faculty Supervisor Name: Marin Soljačić

Project Title: Could an off-the-shelf FPGA beat a state-of-the-art Quantum Computer?

Project Description: Over the course of the XXth and the beginning of the XXIst centuries, the long-standing goal of efficient computing architectures has been investigated by thousands of research teams. The community’s excitement was bolstered by the potential of massive parallelized computation, at an incredible speed and with very low-energy consumption. The last ten years have witnessed the rise of massive data processing techniques and hard optimization problems, mainly driven by their numerous applications in operations and scheduling, drug discovery, finance, circuit design, sensing, manufacturing and social media.

For these applications, the ability to process massive amount of data in parallel has urged on the development of new hardware, like GPUs for Deep Machine Learning implementation and FPGAs. While Moore’s law is petering out, the need for higher computation speed will keep soaring. The impossibility for conventional computers to solve large-scale hard optimization problems (called NP-hard problems) requires the development of application-oriented hardware. For instance, very intricate optical machines have been developed by the research community and by the industry (D-Wave). In this purpose, high-speed, low-power and massively parallel computation are required; three requirements for which FPGA architectures perform much better than their electrical counterpart.

In this project, the UROP student will develop a new scalable, low-power and parallel FPGA process architecture designed to efficiently solve NP-Hard problems. This system will mimic the optical architecture that has been recently developed by the research groups of Profs. Marin Soljačić and Dirk

Englund. In addition to being a very hands-on project, with potential groundbreaking applications in computing, this work presents promising perspectives in application-oriented computing: if fully successful, our approach would enable a routing and delivering company like Amazon to reduce its carbon footprint by several orders of magnitude, or biochemists working on protein folding to decrease their simulation time from several hours today to less than a second and thus facilitate breakthrough discoveries in bioengineering and drug development.

The UROP will be supervised by a graduate student on a weekly basis and will ideally transition to leading this project and come up with new ideas.

Prerequisites: Experience with VHDL and/or FPGA hardware design.

Contact: Charles Roques-Carmes (chrc@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: MIT Quest for Intelligence (QI)

MIT Faculty Supervisor Name: Fraenkel

Project Title:  Machine Learning Approaches to the Study of Neurodegenerative Disease

Project Description: Our group seeks to discover new therapeutic strategies for neurodegenerative disorders through approaches grounded in systems biology.  We integrate diverse information, including genomics, epigenomics, proteomics, metabolomics, clinical and behavioral data.  Using machine learning and network algorithms, we identify potential therapeutic targets for these diseases and refine the models by gathering experimental data in disease models. Current projects include studies of ALS, Alzheimer’s and Huntington’s disease.

Prerequisites: Strong programming skills are essential. Preference will be give to candidates with prior course work in machine learning and/or probability.  While prior coursework in biological subjects is not required, students must be able to pick up relevant biological concepts and facts quickly.

Relevant URL: http://fraenkel.mit.edu

Contact: Ernest Fraenkel (apply.fraenkel@mit.edu)


9/6/18

Term: Fall

UROP Department, Lab or Center: Sloan School of Management (Course 15)

MIT Faculty Supervisor Name: Professor Scott Stern

Project Title: Evaluating MIT REAP Cohort 6 Regional Innovation Ecosystems: Innovation Capacity (I-Cap) & Entrepreneurship Capacity (E-Cap)

Project Description: MIT REAP is looking for an undergraduate student to work on a data collection and research project. The student will use the MIT Innovation Ecosystem Tool, developed by MIT REAP, to collect relevant and accessible data on Innovation Capacity (I-Cap) and Entrepreneurship Capacity (E-Cap) for MIT REAP Cohort 6 regions (incl. Campania, Central Denmark, Guangzhou, Guayaquil, Kentucky, Leeds, Monterrey, Oslo, Sydney). The student will also research and describe the potential factors that cause low numbers on some of the I-Cap and E-Cap metrics collected. After data collection, using the above-mentioned tool, the student will create graphs of Cohort 6 region’s innovation and entrepreneurial ecosystem. The student will work closely with MIT REAP staff and faculty supervisor Prof Scott Stern. The direct manager will be  the Director of MIT REAP.

Prerequisites: Data science background, economics, interest in innovation ecosystems. Experience in data collection and analysis.

Relevant URL: http://reap.mit.edu/

Contact: Nerminka Muslija (nmuslija@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Biological Engineering (Course 20)

MIT Faculty Supervisor Name: Daniel Anderson

Project Title: Formulation of drug-delivery-nanoparticles for the treatment of lung diseases

Project Description: The goal of this project is to formulate drug-delivery-nanoparticles carrying siRNA to target lung endothelial cells. For this project, the student will be responsible for formulating various nanoparticles types, characterizing and testing the efficacy of these nanoparticles, and optimizing the formulation to enhance the nanoparticles' efficacy. Basic background in chemistry and biology is necessary but not mandatory. The student will work directly with a graduate student who will serve as mentor and who will give direction to the project. At the end of the project, the student will have acquired fundamental lab skills and knowledge regarding nanoparticle formulation that will make him/her a competitive student for graduate or medical school.

Prerequisites: Strong desire to work in a research lab. Basic background in chemistry and biology is necessary but not mandatory. A commitment of 10 hrs per week is ideal - hours will vary weekly and the student is not expected to work for more than 10 hours a week.

Relevant URL: https://scholar.harvard.edu/edwardguzman/home

Contact: Edward Guzman (ebguzman@mit.edu)


9/6/18

Term: Fall

UROP Department, Lab or Center: Political Science (Course 17)

MIT Faculty Supervisor Name: Ariel White

Project Title: Collecting data for political science research on protest, incarceration, and media

Project Description: Professor Ariel White is looking for a few UROPs to work on a few projects over the fall semester. The student would work between 5 and 15 hours per week depending on their availability.

Professor White is seeking aid on two projects: (1) a project on policing of Black Lives Matter protests, and (2) a study of how local newspapers talk about crime and race. Tasks on these projects include reading and analyzing newspaper content, coding work of various types, and other duties as assigned.

Please send a resume to Kathryn Treder (ktreder@mit.edu) with a note about your availability this semester-- how many hours per week would you be hoping to work? Additionally, please send along your general availability for an interview.

Prerequisites: There is no required coursework or work experience for this position; applicants should be good at doing repetitive reading or coding tasks carefully.  Work schedules are flexible (no requirement to come into the office or work during business hours, save for occasional meetings).

Contact: Kathryn Treder (ktreder@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Electrical Engineering and Computer Science (Course 6)

MIT Faculty Supervisor Name: Stefanie Shattuck-Hufnagel

Project Title: How do your hands move when you talk?

Project Description: Interested in the gestures that people make when they talk?  This project studies co-speech gestures---the movements that speakers make with their hands, eyebrows, shoulders or upper torso when they talk---and how those gestures line up with the prosody of the speech, i.e. the phrasing and accentuation, and the overall discourse structure.  You will learn to label the gestures and the prosody, and will participate in analysing the results to test hypotheses about the correlations among these different aspects of communication.  This is an opportunity for research engagement---we will value your input and will encourage you to work on the hypotheses you develop. Some experience with data analysis and data sense-making required; you should be someone who pays attention to the long-term value of accurate and well-organized data, as you are labelling. Available for pay or credit.

Prerequisites: Experience with manipulating visual and auditory recordings and some programming is desireable but not required; we can train you.

Contact: Stefanie Shattuck-Hufnagel (sshuf@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: V. Michael Bove

Project Title: Designing new Gestural Interfaces in Mixed Reality

Project Description: With the release of the Magic Leap Creator and Leap Motion NorthStar platform for new mixed-reality and augmented-reality applications, we are creating a new gestural interface for simulating and deploying robots. Our goal is to better understand locomotion in 3D space and diagnose character movement under multiple constraints.

The UROPer will be working under both Media Lab and CSAIL departments. This specific project will focus on the UI design in Unity using the Leap Motion device, which will be built on top of the robotics toolkit developed at CSAIL.

Prerequisites:

  • Unity experience (required)
  • Leap Motion experience

Relevant URL: https://www.media.mit.edu/projects/mixed-reality-robots/overview/

Contact: Vik Parthiban (vparth@mit.edu)


9/6/18

Term: Fall

UROP Department, Lab or Center: Political Science (Course 17)

MIT Faculty Supervisor Name: Regina Bateson

Project Title: First We Marched, Then We Ran

Project Description: The 2018 midterm elections are just around the corner, and record numbers of candidates are running for Congress. Many of these candidates are progressive outsiders who would have never considered running for office, but for the election of Donald Trump. This research project seeks to document and analyze their experiences.

Prof. Bateson is assembling a team of UROPs to assist with research on candidates, to communicate directly with candidates, and to organize a conference of candidates, journalists, and academics, which will be held in January 2019.

Wellesley students are especially encouraged to apply.

The undergraduate researchers will:

  • Gather and code information about candidates for Congress. This will include reviewing campaign finance reports, personal financial disclosures, and other primary-source documents.
  • Find contact information for current and former Congressional candidates, and assist with scheduling interviews with them.
  • Transcribe and code interviews with current and former Congressional candidates.
  • Help to plan and execute a conference of 2018 Congressional candidates. The conference will be held in the greater Boston area in January 2019. This will include providing logistical support, inviting candidates, publicizing the conference, and recruiting journalists and academics to serve as moderators.
  • Attend a weekly team meeting at MIT or Wellesley.

This is a unique opportunity to join a dynamic team working at the intersection of real-world politics and academic research. In 2016, Prof. Bateson was recognized as MIT’s UROP mentor of the year. She was also recently a candidate for Congress in California’s 4th District. 

Prerequisites:

  • Excellent written and oral communication skills.
  • Responsible and reliable.
  • Demonstrates good judgment and has the maturity and discretion to be communicating with current and former political candidates, journalists, and academics.
  • Outstanding organizational skills and attention to detail.
  • Experience working on a campaign or volunteering for a political candidate is an asset, but applicants do not necessarily need to have any political experience or any particular academic preparation.

Note: Liberal, moderate, and conservative students are all encouraged to apply. Diverse viewpoints make teams stronger.

Contact: Regina Bateson (bateson@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Aeronautics and Astronautics (Course 16)

MIT Faculty Supervisor Name: Prof. Jonathan P. How

Project Title: Using holographic glasses for driver-vehicle communication in self-driving cars

Project Description: The Aerospace Controls Laboratory is building an autonomous golf cart shuttle service for MIT campus. We are especially interested in the interaction between self-driving vehicles and humans. For example, we have used Deep Reinforcement Learning to learn how to avoid pedestrians in a socially cooperative manner.

Many people outside research consider self-driving vehicles as scary, because the vehicle acts as a black-box engine. Displaying a distilled form of a vehicle's perception and decision making process could greatly increase the understanding and adoption of self-driving cars. This UROP explores new forms of driver-vehicle communication in the form of holographic glasses to make the driver trust the autonomous car.

Prerequisites:

  • Excited about working with Microsoft HoloLens and ideally having prior exposure to it
  • Experience with Unity and graphical modeling tools: Blender, ...
  • Excited about robots and hands-on experience with ROS (e.g. MIT Racecar class, 6.141,...)
  • Creativity and motivation to bring yourself into the team

Make sure you have 10+hrs/week in Fall and full-time availability in IAP, so we can achieve ours goals together. If you're interested, contact us with your CV and grade report.

Contact: Björn Lütjens (lutjens@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Aeronautics and Astronautics (Course 16)

MIT Faculty Supervisor Name: Prof. Jonathan P. How

Project Title: Converting the hardware of a manual golf car to be driven autonomously

Project Description: The Aerospace Controls Laboratory is building an autonomous golf cart shuttle service for MIT campus. Golf carts will drive on campus, transport people and act as a testbed for navigation algorithms around pedestrians.

This UROP converts the hardware of a manually driven car into being autonomous. This includes motors, wheel encoders, sensor mounts, design and many more modifications / add-ons. The built autonomous vehicle will be constantly navigating around pedestrians, so only quality engineering on the hardware can guarantee for safe navigation.

Prerequisites:

  • Extensive hands-on workshop experience: CNC, water jet, metal work, soldering, 3D printing,...
  • Electronics: Motor selection, ...
  • Knowledge in 3D modeling tools: SolidWorks, AutoCAD, ...
  • Excited about robots and ideally worked with ROS
  • High appreciation of safe and robust systems
  • Creativity and motivation to bring yourself into the team

Make sure you have 10+hrs/week in Fall and full-time availability in IAP, so we can achieve ours goals together. If you're interested, contact us with your CV and grade report.

Relevant URL: http://acl.mit.edu/projects/MOD_Project.html

Contact: Björn Lütjens (lutjens@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Aeronautics and Astronautics (Course 16)

MIT Faculty Supervisor Name: Prof. Jonathan P. How

Project Title: Using RCNNs for pedestrian motion analysis in autonomous vehicles

Project Description: The Aerospace Controls Laboratory is building an autonomous golf cart shuttle service for MIT campus. We are especially interested in the interaction between self-driving vehicles and pedestrians. For example, we have used Deep Reinforcement Learning to learn how to avoid pedestrians in a socially cooperative manner.

The pedestrian-vehicle interaction can further be improved if we analyse the pedestrian posture. Recurrent Convolutional Neural Networks (RCNNs) have shown impressive results on video posture recognition (http://densepose.org/). This UROP improves on current state-of-the-art pose recognition, extracts contaxt information from the poses (such as gaze contact, lifted arm for hailing rides, ...) and finally implements it on a real vehicle.

Prerequisites:

  • Excited about robots and hands-on experience with ROS (e.g. MIT Racecar class, 6.141,...)
  • Experience in Computer Vision (Classes: 6.801/6.866, 6.819/6.869., Tools: OpenCV, PCL, ...)
  • Python programming experience
  • Practice with the workflow and tools of deep learning (tensorflow, theano, ...)
  • Experience with annotation process (Amazon mechanical turk,...)
  • Creativity and motivation to bring yourself into the team

Contact: Björn Lütjens (lutjens@mit.edu)


9/6/18

Term: Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Pattie Maes

Project Title: Contextual memory aids for Alzheimer

Project Description:  We are working on a memory prosthesis system that assists people with Alzheimer's using real-time contextual information in the form of auditory feedback. We seek to reduce stressful and straining situations that can trigger delirium, which has been shown to accelerate cognitive decline in Alzheimer disease.

The current prototype is a wearable composed of a pair of glasses frame equipped with an array of sensors, including a camera, 9-DOF IMU, HR, and EDA sensor. The main application consists of providing relevant information about the person the user is directly interacting with. When the user tilts their head, a photo is taken and classified, providing with the name and relationship the user has with such person.

The next steps of this projects involves identifying stressful situations such as disorientation and confusion using the aforementioned sensors, and then providing appropriate assistance.

Prerequisites: Strong programming, math, and stats background. Signal processing and machine learning (computer vision, data analysis). We're planning on running the models generated on a mobile device, so experience optimizing for constrained hardware would be useful. Knowledge in neuro and cognitive science, embedded systems, and HCI is also useful but not required.

Contact: Tomás Vega (tomasero@mit.edu)


9/6/18

Term: Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: V. Michael Bove

Project Title: Sideways Search computational creativity tool 

Project Description: This semester in the Media Lab’s Object-Based Media group, we’ll be continuing to develop computational design tools that embrace ambiguity and serendipity, vital for technologies used early in the creative process.  We’ll be continuing to develop the Sideways Search inspiration exploration tool (http://pathways.surge.sh/conceptnet/full/), an online browsing tool that seeks to provoke unexpected inspiration and guide pathways to new ideas through providing users with a selection of semi-randomly chosen, loosely related, diverse sources from art, design, history and literature for every search query.  This Fall (and possibly IAP), we’ll be integrating user feedback into modified and new features, such as an ‘image interpolation’ feature that uses machine learning to connect two different images through images with similar visual elements.  There is also opportunity to work on the design(human)design tool (http://designhumandesign.media.mit.edu/), and help build a projection mapping table on which to view these tools in a more immersive environment.

Prerequisites: Skills required:

  • JavaScript (ideally with knowledge of D3 visualization library)
  • Front end web development

Contact: Philippa Mothersill (pip@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Rebecca Saxe

Project Title: Investigating social cognition in adults

Project Description: How do people navigate their social worlds?  Three ongoing projects in SaxeLab examine (1) how we attribute emotions to others, (2) how we experience them ourselves, and (3) how we experience unmet social needs. We are looking for UROPs to help develop experimental stimuli, recruit participants, collect and analyze behavioral data, and assist with fMRI scans this semester.  UROPs will also have the opportunity to attend weekly lab meetings where we hear from speakers and discuss current research topics. A successful UROP will have good organizational skills and be willing to interact with adult subjects. Please indicate any prior experience in video editing or data analysis and any preference in the above mentioned studies. There may be the possibility to continue into the spring semester with any of the three projects.

The UROP will be expected to perform the following tasks:

  • Recruit participants
  • Help with data collection and analysis
  • Help prepare experimental stimuli
  • (Optional) Attend weekly lab meetings

Prerequisites:

  • Good organizational skills
  • Commit to 10 hours/week

Contact: Ben Mittman (bmittman@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Chemical Engineering (Course 10)

MIT Faculty Supervisor Name: Michael Strano

Project Title: Building and Characterizing Carbon Nanofluidic Devices for Energy Efficient Separation and Transport

Project Description: Carbon nanotubes (CNTs) are atomically thin cylinders of carbon that are around 1 nm in diameter and can reach lengths of up to 1 cm. These materials are noteworthy for their strength, rigidity, and electrical properties. They are also noteworthy as conduits for fluid flow, particularly for so-called “slip flow” that is thousands of times faster than Hagen-Poiseuille flow and violates the no-slip boundary condition. Because of the flow enhancement enabled by molecular confinement, carbon nanotubes could form the basis for a new class of nanofluidic devices for biomolecule (DNA/RNA) sequencing, energy-efficient separations, or ion transport and detection. In order to realize these applications, it is necessary to understand how water and other liquids enter carbon nanotubes, and how these filling events can be induced.

As a student on this project, you will grow carbon nanotubes through chemical vapor deposition (CVD) and characterize whether they are filled or empty using Raman spectroscopy, a laser-based technique. While the project is quite open-ended, and I look forward to developing a series of experiments in more detail with you as we go forward, the project initially will involve testing CNTs of different sizes with different liquids and pre-treatments to optimize the likelihood of nanotube filling/emptying.

You will have the opportunity to interact with many graduate students and postdocs in a large, interdisciplinary lab; learn important laboratory techniques including Raman spectroscopy, fluorescence spectroscopy, chemical vapor deposition, scanning electron microscopy, and more; and work on a project and in a lab with connections to medicine, energy, water purification, and nanotechnology. I look forward to hearing about your interests and what you would like to achieve during your research experience.

Prerequisites: Students with plan for year-long or longer research commitment with interest in chemistry, fluid mechanics, nanomaterials, or research with energy applications. Experience using Matlab is a plus. Applications will be considered until 9/15/18.

Relevant URL: srg.mit.edu

Contact: Samuel Faucher (sfaucher@mit.edu)


9/6/18

Term: Fall

UROP Department, Lab or Center: Science, Technology, and Society (STS)

MIT Faculty Supervisor Name: John Durant

Project Title: Developing Intuitive Interface Hardware for Complex Path Generation for Robotic Arm

Project Description: Industrial robotic arms are typically used highly controlled environments. As a result, their interfaces are focused on highly structured implementations where complex paths are calculated once in a simulated environment and then repeated many times on the actual robot. However, there are cases in which the frequent changing and updating of paths is desirable. Often a user could benefit from the assistance of a robotic arm on a task, but the time to program a complex motion is too high to justify its utility.

The goal of this project is to extend Blender with a toolset tailored for the nuanced control of robotic arm path generation. Blender has been chosen because of its open source nature and its built in IK solver which is being used to simulate a UR5 collaborative robotic arm. Keyframing has proven to be a powerful tool for constructing and constraining nuanced robotic motion but the editing tools in blender are not optimized for path generation and manipulation. Additionally there are significant animation limits that constrain the current allowable path length. 

Prerequisites:

  • Intermediate experience programming (Python and/or C++).
  • Experience working with Processing and/or Pure Data
  • Intermediate Blender proficiency. Experience with IK rigging for animation is a plus.
  • Experience using Adobe Illustrator or equivalent.
  • Basic understanding of keyframing.
  • Interest in developing robust and intuitive GUIs.

Contact: Adam Burke (aburke3@mit.edu)


9/6/18

Term: Fall

UROP Department, Lab or Center: Science, Technology, and Society (STS)

MIT Faculty Supervisor Name: John Durant

Project Title: Developing Intuitive Interface Software for Near Real-Time Path Generation for Robotic Arm 

Project Description: Industrial robotic arms are typically used highly controlled environments. As a result, their interfaces are focused on highly structured implementations where complex paths are calculated once in a simulated environment and then repeated many times on the actual robot. However, there are cases in which the frequent changing and updating of paths is desirable. Often a user could benefit from the assistance of a robotic arm on a task, but the time to program a complex motion is too high to justify its utility.

The goal of this project is to develop a tool or set of tools that allow for the generation in near real time, recording, and repetition of complex and nuanced three-dimensional paths with a motion tracking device and intuitive user interface. These tools will be implemented in conjunction with a UR5 (6 degrees of freedom) collaborative industrial robotic arm. There are a wide range of approaches for motion tracking that can be explored based on experience and interest.

Prerequisites:

  • Experience programming (URScript has a Python-like syntax)
  • Experience and interest in working with physical computing systems
  • Basic understanding of robotic kinematic control
  • Basic understanding of TCP communication
  • Familiarity with UR collaborative arms is a plus, but not required.

Contact: Adam Burke (aburke3@mit.edu)


9/6/18

Term: Fall

UROP Department, Lab or Center: Chemical Engineering (Course 10)

MIT Faculty Supervisor Name: Langer

Project Title: Large-scale film generation for drug delivery

Project Description: We are currently developing novel films from natural material for various medical applications. Since properties of the film vary drastically depending on the mode of production and adjuvants, we are aiming to stratify large-scale film generation and mechanical testing with advanced data analysis methods. Films will be generated with various additives and will be further processed and tested for their mechanical and physical properties. Main responsibility by the student will be film preparation, processing, and mechanical testing - both autonomously as well as together with the team here at the lab. The project aims to generate novel, biocompatible films with desirable property profile for medical applications and in vivo testing. Work will be conducted in the Langer Lab in the Koch Building for the Fall 2018.

Please send you resume/CV to Dr. Giovanni Traverso, cgt20@mit.edu, and Dr. Daniel Reker, reker@mit.edu

Prerequisites:

  • No pre-requisites. We invite applicants from Material Science, ChemE,
  • Biological Engineering, Chemistry, HTS. Interest in material design and mechanical testing a plus.
  • Student expected to be motivated to work in a team and great communication skills.

Contact: Daniel Reker (reker@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Aeronautics and Astronautics (Course 16)

MIT Faculty Supervisor Name: Leia Stirling

Project Title: Muscle activity during a modified lower-extremity executive function task

Project Description: Currently there is not a good understanding of what innate factors affect human adaptability to exoskeleton use. We are putting subjects through a series of cognitive, perceptual and motor tests to quantify these abilities and subsequently measure their adaptation to a powered ankle exoskeleton. One of these cognitive tests is a modified Simon task that quantifies executive function. Traditionally done with subjects’ responding to arrows on a computer screen with a keyboard, we modified this to have subjects respond to vibratory stimuli with their feet to make it more relevant to lower-extremity exoskeleton use. A UROP will analyze electromyography data to explore muscle activity during the modified Simon task.

Prerequisites: Prefer 3rd or 4th year students, experience with MATLAB and/or signal processing is a plus

Relevant URL: http://hsl.mit.edu/

Contact: Aditi Gupta (adgupta@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Electrical Engineering and Computer Science (Course 6)

MIT Faculty Supervisor Name: Richard Fletcher

Project Title: Raspberry Pi and IoT Development for Health Applications

Project Description: Our group is building networked health appliances (furniture, mirrors, street signs, etc.) that can be used to collect health information from a person and transmit it to the cloud for processing. Since we do not want to be limited by the hardware constraints of Amazon Alexa or Google Home, we have been building our own devices which interface to the Raspberry Pi and then communicate with external servers. Raw data includes sound, light, and other information.  We are looking for student(s) who are interested in helping to build some prototype devices and software platforms.

Prerequisites: We are looking for a variety of students to join our team: 

  • (1) students who have experience working in embedded systems, such as programming the Raspberry Pi or working with embedded Linux, who could help implement some of the machine learning algorithms that our group has developed; 
  • (2) we also welcome any students with hardware experience who are interested in helping test some of our wireless sensors and devices that interface with the Raspberry Pi;
  • (3) students with server development experience, interested in developing server API's and architectures to analyze the data from our "health appliances".

Relevant URL: http://www.mobiletechnologylab.org/portfolio/

Contact: Richard Fletcher (fletcher@media.mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Electrical Engineering and Computer Science (Course 6)

MIT Faculty Supervisor Name: Richard Fletcher

Project Title: Mobile Video Game Development for Mental Health Screening 

Project Description: Mental health is an important concern which touches most of our lives, yet this aspect of our health is often neglected. While there are many specific mental health disorders, our group has been developing a mobile-phone based video game as a tool to help people monitor and assess their mental health. We are designing games that test specific neurocognitive measures such as fatigue, working memory, stress level, cognition, and impulsivity. Our goal is to create mobile tools that are fun to use and can function as screening tools as well as biofeedback to help increase our self-awareness. Since very few commercially available mental health apps are actually clinically validated, Our research plan includes rigorous clinical testing of the tools we develop. Our lab has a strong connection to the psychology and behavioral medicine community as well as affiliation with UMass Medical School department of Psychiatry.

Prerequisites: We are seeking students with software and mobile programming skills, who may also have an interest in psychology or mental health, and who are motivated to create new ways to revolutionize mental health assessment and treatment. Our initial video game prototypes have been developed using a specific cross-platform framework called LibGDX (https://libgdx.badlogicgames.com/); however, we are open to using other development tools if the student has strong experience and motivation. Background in mobile app development or video game development experience and graphics is desired.  At this time, we are interviewing students for Fall Semester with the option to continue into IAP or beyond.  We seek someone who is self-motivated and able to work independently, and attend weekly group meetings to check on progress.

Pay or credit is available or UAP project consideration.

Relevant URL: http://www.mobiletechnologylab.org/portfolio/

Contact: Richard Fletcher (fletcher@media.mit.edu)


9/6/18

Term: Fall

UROP Department, Lab or Center: Chemical Engineering (Course 10)

MIT Faculty Supervisor Name: T. Alan Hatton

Project Title: Continuous flow platform via electrochemical adsorption for brackish water treatment

Project Description: Electrochemical adsorption is a promising technique for brackish water treatment and extends the capability of capacitive deionization (CDI) with higher salt adsorption capacity and selectivity. We have built a continuous flow electrochemical adsorption system with online sensors to monitor the conductivity and pH of the effluent stream. The focus of the current project is to utilize the online sensors to:

  • 1. extract important metrics quantitatively, such as the concentration of target molecule by UV-vis spectroscopy and the adsorption rate by a multi-channel potentiostat
  • 2. compare the results with transport modeling, and fit the data to obtain kinetics parameters

The UROP will work closely with a graduate student mentor to learn electrochemical techniques, such as cyclic voltammetry, chronoamperometry and electrochemical impedance spectroscopy, as well as online sensing methods, such as UV-vis spectroscopy and electrical conductivity together with real-time data acquisition using Labview.

Credit or pay is available. It is highly preferred that candidates contact MIT direct funding for pay.

Prerequisites: Candidates from chemical engineering, chemistry and material science or other relevant background are welcome to apply. Previous experience in research lab is preferred. Ability to learn and master new technique quickly. Knowledge with UV-vis spectroscopy is recommended.

Contact: Fan He (fanhe@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Political Science (Course 17)

MIT Faculty Supervisor Name: Charles Stewart III

Project Title:  Data Scraping in Election Science

Project Description: The need for science and transparency in the analysis of elections is an increasingly important part of our democracy. As the MIT Election and Data Science Lab (MEDSL) continues to grow we are are working towards the goal of becoming the foremost clearinghouse for election science data. Although much data exists, it is often hard to access and out of date. This UROP is an opportunity to be part of improving access to data and contributing to election science research.

As a UROP working on this project you will:

  • Closely monitor the general elections in November and develop knowledge of election returns dissemination across the states and DC
  • Collect and organize election science data by building tools to scrape websites
  • Conduct code audits in Python and R
  • Present interesting research ideas and findings to the larger group
  • Learn additional data management and statistical programming skills
  • Contribute to ongoing MEDSL research projects
  • Work towards answering your own research questions related to election science
  • Participate in weekly lab meetings

Prerequisites: Web scraping experience using Python is required.  Experience with R is also desired. Experience contributing to an open source project is preferred. You should also be familiar with data management in formats such as comma/text delimited and/or Excel-type spreadsheets. Additional programming or statistical software skills (e.g., Stata) are desirable but not required. Please indicate your level of familiarity with data collection and management, web scraping, and web architecture when you apply. We welcome applications from students at both MIT and Wellesley. The UROP can be for credit or pay.

Relevant URL: electionlab.mit.edu

Contact: Dr. Cameron Wimpy (wimpy@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Rebecca Saxe

Project Title: Infant neuroimaging with fMRI and fNIRS

Project Description: How does social cognition develop?  Three projects in SaxeLab examine (1) the brain systems that prompt attention to informative people, (2) how babies interact with helpers and hinderers, and (3) the development of brain regions that support high-level vision.  We are looking for UROPs who are eager to work with babies to assist in collecting data using fNIRS and fMRI and to recruit subjects into these studies.  UROPs will also have the opportunity to attend weekly lab meetings where we hear from speakers and discuss current research topics.  A successful UROP will have good interpersonal and organizational skills and be willing to interact with babies and their families.  UROPs will also have the opportunity to learn technical aspects of data collection and analysis.  Please indicate any prior experience working in MatLab and working with babies, children, and families.

The UROP will be expected to perform the following tasks:

  • Recruit participants
  • Help with data collection and data entry
  • Interact with infants and/or children aged 3 weeks to 3 years
  • (Optional) Attend weekly lab meetings

Prerequisites (if any):

  • Prior experience with infants and young children
  • Commit to 10 hours/week

Contact: Ben Mittman (bmittman@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: History (Course 21H)

MIT Faculty Supervisor Name: Jeffrey Ravel

Project Title: Ethnographic Atlas of Nepalese Music

Project Description: MIT, in the context of the MIT-Nepal Initiative, would like to partner with Professor Lochan Rijal of Kathmandu University (Nepal) to develop an online Ethnographic Atlas of Nepalese Music.  Rijla and his students have been gathering recordings and data on ethnic musical traditions throughout the Himalayan country, and would like to partner with MIT to make these resources freely available online.

Prerequisites: Video-editing and web design skills are desirable. Musical talent and an interest in South Asian ethnic musical traditions desirable.  Knowledge of the Nepali language would be useful, but not required.

Relevant URLs:

Contact: Jeffrey Ravel (ravel@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: MIT Quest for Intelligence

MIT Faculty Supervisor Name: Marin Soljacic

Project Title: Artificial Intelligence for Scientific Exploration, Discovery, and Understanding

Project Description: In the last decade, we have witnessed enormous progress in applications of artificial intelligence (AI) for a wide variety of different tasks, including natural language processing, image recognition, self-driving cars, and playing games. We want to investigate how some of these recent AI techniques can be used for scientific discovery. We want to move away from pure data-science approaches since many current deep learning techniques lack interpretability or generalizability (extrapolation outside of the training data set). Rather, we want to more closely integrate physics and machine learning to extract interpretable parameters and derive generalizable laws of nature. The main goal of this project is to develop new AI tools to support scientific discovery in broad areas of science and engineering through automated optimization of experiments, designs, and data analysis techniques.

Our datasets are generated from a variety of systems in physics and engineering, including Maxwell’s equations (electrodynamics), diffusion equation, Navier-Stokes equations (fluid dynamics), and Schrodinger’s equation (quantum mechanics).

Each undergraduate student will have their own project supervised by a graduate student, and will ideally transition to leading the project and come up with new ideas. Students will learn about a variety of modern deep learning techniques.

Prerequisites: Comfort with programming is required. Any major of any year is welcome. Prefer experience with machine learning and Python. Exposure to deep learning, Tensorflow/Pytorch, optimization, differential equations, numerical simulation, and/or Bayesian statistics is helpful, but not required.

Relevant URL: http://www.mit.edu/~soljacic/AI.html

Contact: Samuel Kim (samkim@mit.edu)


9/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Guoping Feng

Project Title: Localization of animal sounds using microphone arrays

Project Description: In our lab we study vocal interaction between animals in the context of social behavior monitoring for neuroscience research related to autism. We are exploring the use of microphone array technology to localize vocalizations. Although various methods of source localization have been  described in the literature, to get the desired result, the choice of methods as well as the hardware and software implementation need to be tailored to each new set of conditions. Reverb, distance of the sources, noise level, bandwidth and number of possible sources, all play a role. The UROP in this project will investigate and try to come up with an analysis that produces accurate localization. Test recordings with ground truth to evaluate the performance of algorithms will be available.

Prerequisites: Strong signal processing skill

Contact: Rogier Landman (landman@mit.edu)


9/4/18

Fall 2018

Department/Lab/Center: Urban Studies & Planning

Faculty Supervisor: Jinhua Zhao

Project Title: Coding an automated texting Chatbot to communicate with participants in a study that will provide discount MBTA cards to low-income Bostonians.

UROP job description: Want to learn how to code ChatBots in a real-world setting? We are looking for one or two UROPs to join our research team. UROPs will help with the coding of an automated SMS/texting Chatbot to interact with study participants. We are using the platform http://motion.ai and have the core of the ChatBot already programmed. Motion.ai provides a nice user-interface for designing the ChatBot and programming is done in Node.js. The ChatBot connects to a SQL database. Motion.ai is now part of the http://hubspot.com company which has launched “Hubspot Conversations”—the UROPs will help transition the ChatBot to the new platform. The UROP will also have the opportunity to help with other aspects of the research project as needed.

Research Study Description: We will be running a 2-month study involving 500 Boston transit riders in Fall 2018. The research project consists of conducting a random-control-trial where half the participants receive a discounted CharlieCard, and the other half a regular CharlieCard. We will track transit usage and see if the intervention changes travel behavior. We will also collect a daily travel diary using an automated ChatBot texting system. Though many low-income residents own a mobile phone, many do not have a data plan. Therefore, texting is preferred over smartphone apps as a method to engage with participants. 

Research purpose: Policymakers and advocates are increasingly concerned with the impacts of growing inequity on the poor and underserved. The burden of transportation costs on the poor is increasing, limiting access to important goods and services, such as medical care, health food options, and training programs. With the poorest in urban areas relying mainly on public transportation, it is central to the discussion of equity. Rapidly increasing public transportation fares across the US is making accessibility more and more unaffordable for low-income riders. Despite these concerns, relatively little is known about how low-income households manage their transportation costs while also preserving their desired level and quality of mobility. When low-income households do find ways to cover their transportation expenditures, many of these strategies create hardship. The objective of the research is to gain insights into changes in travel patterns and quality of life of the participants. 

More information about the project: https://tinyurl.com/MITlowincomefareRCT 

Prerequisites: Programming experience is required. You don’t already need to know Node.js, you can learn it when you start. But you must be a reasonably competent coder. Experience with databases is a plus. Must be comfortable working with APIs. The UROP should be interested in learning new things on their own. An enthusiasm in public transportation and social equity a plus. 10-15 hours per week.

Lab URL: https://mobility.mit.edu/ 

Contact Name: Jeff Rosenblum: jeffreyr@mit.edu


8/31/18

Term: Fall/IAP

UROP Department, Lab or Center: Health Sciences and Technology (HST)

MIT Faculty Supervisor Name: Elazer Edelman

Project Title: Modeling physiological shock states to study endothelial cell heterogeneity

Project Description: The objective of this work is to improve the management of cardiovascular shock states by studying the effect of different shock types on endothelial cells, which line the walls of blood vessels throughout the body. Previous work in our lab has identified heterogeneity in the response of these cells to environmental stimuli using single-cell transcriptomics and imaging-based methods. This project will apply environmental drivers of shock including flow alteration and inflammation to flow-cultured endothelial cells. This work is particularly relevant to students interested in medical applications of research. Students will be exposed a range of lab techniques including static cell culture, in vitro flow conditioning, and cellular imaging. Additionally, UROPs will have the opportunity to be involved in application of modern single-cell transcriptomics methods and computational analysis of resulting data.

Prerequisites: The ideal candidate will have previous experience working in a wet lab (ex. cell culture and experience with some of the techniques listed above). Must be able to commit 5-10 hours per week during fall semester. A background in biology, bioengineering, physiology, or related fields is desired but not required.

Relevant URL: edelmanlab.mit.edu

Contact: Aditya Kalluri (askallur@mit.edu)


8/31/18

Term: Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Canan Dagdeviren

Project Title: Interfacing Microelectromechanical Sensor for Soft Tissue Biomechanics Monitoring

Project Description: We are developing a microfabricated sensor for monitoring soft material stiffness with potential implantable applications. This UROP position is focused on developing the interfacing electronics and the student will be working closely with the graduate mentor in the followings:

  1. Development of compact interfacing circuit for extraction of microvolt signal
  2. System integration

Representative literature: https://www.nature.com/articles/nmat4289

Prerequisites: Prerequisites: Dedicated and responsive. Have basic concepts of analog circuit design and related hands-on experience. Knowledge in one of the followings is a plus: signal-integrity, finite element modeling, low-voltage signal extraction.

Relevant URL: https://www.media.mit.edu/projects/conformal-implantable-viscosity-and-electrochemical-sensors/overview/

Contact: Zijun Wei (zijunw@mit.edu)


8/31/18

Term: Fall/IAP

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Dick K.-P. Yue

Project Title: Fast Computation of Phase-Resolved Ocean Waves in CPU/GPGPU Environments for Ocean Wave Energy Systems

Project Description: Real-time computing of phase-resolved ocean wave environments from sensor data requires the ability to obtain fast reconstruction and prediction of the phase-resolved wave field with computations distributed over a network of mobile (sensing) platforms.  In recent years, we have developed nonlinear phase-resolved simulations for large domains.  Such computations are, however, based on a single large HPC platform with the assumption that all sensing data are synchronously available on the platform.  In the context of this project, this is not realistic nor scalable.

The overall objective of this part of the research is to convert our phase-resolved simulation capability for real-time computations over a network of CPU-GPU heterogeneous hardware.  The UROP project will be to develop, test and benchmark the kernels necessary for the GPU implementation of the algorithm.

Role: The initial responsibilities of the UROP will be to develop the GPU kernels necessary for modular implementation of the numerical algorithm. This includes benchmarking the robustness, accuracy and comparative efficiencies.  Future responsibilities can include work towards incorporating the modules the full CPU-GPU algorithm.

Prerequisites: Open to all majors of any year. Strong experience in CUDA/OpenCL programming is required.  Interest or experience in any of the following is preferred: Fortran programming, the study of waves and wave body interactions, and ocean wave energy systems.

Contact: Kelli Hendrickson (khendrk@mit.edu)


8/31/18

Term: Fall and IAP

Department/Lab/Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Ann Graybiel

Project Title: Mouse models of movement disorders

Project Description: We are seeking a student to help full-time this summer with continuation during the academic year. The research involves histological and behavioral studies of mouse models of movement and motivational disorders such as Parkinson's and Huntington's disease. We have generated transgenic mice to visualize and control forebrain circuits that degenerate in these disorders and that normally control movement and mood. The position available involves studying behavioral and molecular effects of these new transgenic manipulations in mice. The experiments require a a significant amount of training and dedicated time in the laboratory and so we are seeking a student that will be able to continue research in the Graybiel laboratory for longer term.

Prerequisites: N/A

URL: http://www.graybiel-lab.com/

Contact: Jill Crittenden: jrc@mit.edu


8/29/18

Term: Fall/IAP

UROP Department, Lab or Center: MIT Quest for Intelligence (QI)

MIT Faculty Supervisor Name: Josh Tenenbaum

Project Title: Learning as Program Induction

Project Description: This posting is for a set of artificial intelligence and cognitive science projects. These projects focus on modeling human learning as program induction: learning computer programs from data. They would involve contributing to large-scale learning systems, whose inputs might be things like images, planning problems, or sequence transformations, and whose output would be a program computing these images, plans, or transformations. We are looking for help in developing software implementing these systems as well as help developing and running behavioral experiments to compare them with humans.

MEng EECS students are especially encouraged to get in touch with us.

Prerequisites:

Applicants should have:

  • Background in artificial intelligence (AI), machine learning (ML), and/or programming language theory (PLT);
  • Software engineering experience, having contributed to mid-sized or large-scale software projects (e.g. familiar with unix, git, a text editor, testing & documenting code);
  • Experience working with python and/or functional languages, especially ocaml or rust; and
  • An interest in learning systems motivated by cognitive science and human psychology.

Individuals with strong backgrounds in the following areas should also consider applying:

  • Deep learning
  • Distributed and parallel computing
  • Program synthesis
  • Cognitive science

Contact: Josh Rule (rule@mit.edu)


8/29/18

Term: Fall/IAP

UROP Department, Lab or Center: Electrical Engineering and Computer Science (Course 6)

MIT Faculty Supervisor Name: Jorg Scholvin

Project Title: Intelligent Embedded Systems for Complex Equipment Monitoring

Project Description: A UROP position is available at MIT.nano and EECS, working under the guidance of the Assistant Director of User Services at Fab.nano, to develop IoT‐style systems that monitor and analyze the state and performance of complex nanofabrication equipment.

The project aims at developing a network of Raspberry‐Pi based measurement systems, which will acquire data continuously from sensors placed on or around nanofabrication equipment. The research will involve embedded programming (to communicate with sensors), touchscreen GUI development on Raspberry Pi, database storage and web interfacing to view analyses, and the development of algorithms to infer tool performance and health; both in real‐time (at the tool) and lab‐wide. Work will be conducted both off‐site (coding) and inside of MIT.nano (testing and deployment in the labs).

Prerequisites: A strong candidate would have a solid programming background, and several of the following skills and interests:

  • (A) software: embedded systems (Python, Ubuntu, Raspberry Pi, I2C or SPI protocols, Arduino, Bluetooth, RFID), GUIs for touchscreens, time‐series data processing & display (using suitable Python libraries), basic cyber security, data storage and databases.
  • (B) analysis: basics of signal processing and/or machine learning on time series data.
  • (C) hardware: basic knowledge of electronic circuits and embedded systems, and familiarity with different types of sensors (e.g. temperature, vibration, optical, etc.) and their basic measurement principles. Prior class or other exposure to microcontrollers is helpful but not required.

Qualified applicants must have a strong work ethic, be detail oriented, reliable, and work well with others. This will be a full‐time project during IAP, and we require on average 15‐20 hours/week during the fall and spring semesters, with an opportunity to continue full time over the summer in 2019. Projected start date is early October. We are open to a multi‐year commitment as that can result in co‐authorships and publications, MEng work, or even start‐up opportunities.

Contact: Jorg Scholvin (scholvin@mit.edu)


8/29/18

Term UROP is offered: Fall

UROP Department, Lab or Center: Comparative Media Studies (21 CMS)

MIT Faculty Supervisor Name: Eric Klopfer

Project Title: Mobile Participatory Simulation Games

Project Description: Interested in games?  Want to work in web and app development? Apply to work on Participatory Simulations in STEP/TEA as a UROP!

Over many years and many iterations of technologies (from Palm Pilots to iPhones) we (Scheller Teacher Education Program and The Education Arcade) have been working on whole class systems-based mobile simulation games. Imagine a classroom game in which you must interact with others but avoid getting contaminated with a virus being passed around.  OR trying to maintain the balance in a classroom digital ecosystem while keeping yourself alive. These are just some of the scenarios we’ve developed over the years with a lot of success.

The latest iterations of these games are being designed for mobile devices including smartphones and tablets using portable technologies (React).  We are looking for UROPs to help design new iterations of these games and implement them using scalable web technologies.

The system is currently a beta version using React (js) and Firebase. This Fall we plan to bring that beta to a release, design and implement at least one new game, and add a React native client.

If you are interested in this position, please send an email to tea-jobs@mit.edu and include:

  • * an overview of your programming experience (specific references to relevant courses and other development and programming projects would be very helpful) including any pertinent URLs
  • * a summary of any previous UROP and work experience (attach a resume if you have one)
  • * a short description of why you are interested in working on this project
  • * Please put “PSims" in the subject line

Prerequisites: We are looking for students with a strong programming background.  Experience with JavaScript/HTML/CSS, React/Redux/React Native and NoSQL databases is helpful.  Interests/expertise in front end design and game design are also big strengths.  Availability to work some hours at the STEP/TEA Lab is required.

Contact: Eric Klopfer (klopfer@mit.edu)


8/29/18

Term UROP is offered: Fall/IAP

UROP Department, Lab or Center: Chemistry (Course 5)

MIT Faculty Supervisor Name: Daniel Anderson

Project Title: Synthesis and evaluation of lipid nanoparticles for gene delivery

Project Description: Gene therapy is a promising treatment strategy and has the ability to regulate protein concentrations at the cellular level. Development of delivery strategies is critical in realizing their full clinical potential. In the current study, we want to design, synthesize and biologically evaluate the lipid nanoparticles that can deliver short interfering RNAs or messenger RNAs.

Keywords: drug delivery, gene therapy, organic chemistry

Prerequisites: Organic chemistry 1 and 2. Hands on experience in organic chemistry and molecular biology.

Relevant URL: http://anderson-lab.mit.edu/

Contact: Chandra Bhattacharya (cbhattac@mit.edu)


8/29/18

Term: Fall/IAP

UROP Department, Lab or Center: MIT Quest for Intelligence (QI)

MIT Faculty Supervisor Name: Nicholas Roy

Project Title: AI Software Development for the Bridge

Project Description: The possible projects will span helping implement software and infrastructure as part of MIT’s Quest for Intelligence. The goal of the projects is to develop the necessary software services and infrastructure that allow artificial intelligence to accelerate research and education.  Potential responsibilities include designing, implementing, testing, and maintaining software infrastructure for machine learning, data discovery, and inference, including data logging, visualization, test infrastructure, continuous build-and-test services, inter-process communication, and embedded firmware; implementing, testing, and maintaining data processing pipelines; collaborating on establishing software pipelines and infrastructure to use AI and ML tools to accelerate research and education practices; integrating software from campus research groups and contributing data and algorithms; maintaining up-to-date awareness of and sharing relevant best practices in software engineering; developing high quality code and working to ensure code quality across the system; establishing goals and remaining on schedule.

Prerequisites: Not required but will be significantly helpful: programming experience in Python and C++; experience with machine learning software development and engineering practices, including TensorFlow, Caffe, and PyTorch; experience with GPU programming, including OpenCL and CUDA; experience with software development practices, including git-based version control and continuous integration; experience integrating with large cloud service providers.

Relevant URL: quest.mit.edu

Contact: Josh Joseph (jmjoseph@mit.edu)


8/29/18

Term: Fall

UROP Department, Lab or Center: MIT Quest for Intelligence (QI)

MIT Faculty Supervisor Name: Aude Oliva

Project Title: Crowdsourcing attention and interestingness of images

Project Description: Where do people look in images, what do they find interesting in graphic designs, and how do they explore 2D and 3D scenes? This project aims to capture human attention on different types of images through interactive crowdsourcing tasks, on the web and on mobile. Aspects of this project include building user interfaces for large-scale crowdsourcing experiments, statistical data analysis, and machine learning to build

predictive models of attention and visual exploration. Applications include smart image compression, automatic thumbnailing, and personalized graphic designs. This project lies at the interface of human vision, computer vision, and HCI.

Prerequisites:

  • Required: proficiency with python, javascript, html, jquery.
  • Recommended: 6.148, 6.170 or similar.
  • Bonus: 6.036, 6.819, or similar.

Relevant URL: http://cvcl.mit.edu/publications.html

Contact: Zoya Bylinskii (zoya@mit.edu)


8/29/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Ann M. Graybiel

Project Title: Computational and mathematical analysis of decision-making in a mouse model of a neurodegenerative disease

Project Description: Use your computational and mathematical skills to solve the mysteries of the brain! Using cutting-edge statistics, modeling, machine learning, optimization, image processing, and/or other methods, you will assist us in analyzing recordings of brain activity in Huntington's disease model mice obtained using calcium imaging with genetically encoded GCaMP6 indicators. Students with strong programming and mathematics skills majoring in Courses 6, 7, 8, 9, 18, 20 and other majors are welcome. We focus on the striatum, which is a key part of the basal ganglia, receiving input from midbrain dopamine neurons, cortex, and thalamus. It is thought to be centrally involved in evaluation, selection, motivation, and decision making, not only at the level of movements but also at the level of goals, strategies, thoughts, emotions, and sensory interpretations. It is implicated in movement disorders like Parkinson's disease, Huntington's disease, and dystonia, as well as addiction, depression, attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), Tourette syndrome, autism spectrum disorders, aspects of schizophrenia, and other disorders.

Prerequisites: No prior experience is required, but you must be highly motivated and conscientious. We will give preference to students who can commit to working for a year or more for at least 12 hours per week during the fall and spring semesters and 20 to 40 hours per week during the summer and IAP. Times are flexible; evenings and weekends are available. We can usually only provide academic credits (not payment) for new UROPs.

Relevant URL: http://graybiel-lab.mit.edu/

Contact: Leif Gibb (lgibb@mit.edu)


8/29/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Ann M. Graybiel

Project Title: Brain activity during decision-making in a mouse model of a neurodegenerative disease

Project Description: Help us do experiments to solve the mysteries of the brain! In this project, you will literally see the cells lighting up in the brains of mice and help us figure out the functions of different cell types in the striatum. You will assist us in performing experiments recording brain activity in Huntington's disease model mice using the cutting-edge technique of calcium imaging with genetically encoded GCaMP6 indicators. You may help us run experiments, perform neurosurgeries, train animals and/or build micro-devices for recording neural activity. In the future, there may be opportunities to perform experiments manipulating neural activity and behavior using optogenetics. Students with strong programming and mathematics skills may also assist in data analysis. 

This is an excellent UROP for students seeking laboratory experience in preparation for medical school or a research PhD program. Students majoring in Courses 6, 7, 8, 9, 18, 20 and other majors are welcome. We focus on the striatum, which is a key part of the basal ganglia, receiving input from midbrain dopamine neurons, cortex, and thalamus. It is thought to be centrally involved in evaluation, selection, motivation, and decision making, not only at the level of movements but also at the level of goals, strategies, thoughts, emotions, and sensory interpretations. It is implicated in movement disorders like Parkinson's disease, Huntington's disease, and dystonia, as well as addiction, depression, attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), Tourette syndrome, autism spectrum disorders, aspects of schizophrenia, and other disorders.

Prerequisites: No prior experience is required, but you must be highly motivated, conscientious and detail oriented. We will give preference to students who can commit to working for a year or more for at least 12 hours per week during the fall and spring semesters and 20 to 40 hours per week during the summer and IAP. Times are flexible; evenings and weekends are available. We can usually only provide academic credits (not payment) for new UROPs.

Relevant URL: http://graybiel-lab.mit.edu/

Contact: Leif Gibb (lgibb@mit.edu)


8/29/18

Term: Fall/IAP

UROP Department, Lab or Center: Chemical Engineering (Course 10)

 

MIT Faculty Supervisor Name: Michael Strano

 

Project Title: Sensor Design for the Detection of Heavy Metal Contamination in Fish and Water

Project Description: Rare earth mineral mining was resulted in the increase of heavy metal contamination in fresh water supply and consequently in freshwater aquatic products. Especially in developing countries with less aggressive regulation, much of the risks is passed onto the local consumer. Conventional detection techniques for these contaminants require a laborious process that is both time and resource consuming. This project aims toward the development of a portable nanosensor platform for heavy metals and other contaminants. One area of Prof. Strano’s laboratory focuses on the engineering SWCNTs as specific biosensors for reactive species, small molecules and proteins. We have discovered a system coined corona phase molecular recognition (CoPhMoRe) where analytes can be specifically identified using its interactions with the external surface of a nanomaterial. This work will extend the technology of CoPhMoRe toward the targeted detection of heavy metal ions in water supply and freshwater fish.

As a student on this project, you will be exposed to a very diverse and interdisciplinary research project and lab. You will have the opportunity to learn many different areas of research ranging from synthesis and characterization of our bionanosensors, study of nanomaterial activity and structure, testing of sensitivity and specificity of the SWCNTs, and potential work with cell culture.  Students will also have the opportunity to learn characterization techniques such as fluorescence spectroscopy, absorption spectroscopy, Raman spectroscopy, circular dichroism and isothermal calorimetry.

Prerequisites: Students with plan for year-long or longer research commitment with interest in biology, chemistry, bioengineering, or nanomaterials. Applications will be considered until 9/15/18.

Relevant URL:  srg.mit.edu

Contact: Xun Gong, MD, PhD (xungong@mit.edu)


8/29/18

Term: Fall/IAP

UROP Department, Lab or Center: Chemical Engineering (Course 10)

MIT Faculty Supervisor Name: Michael Strano

Project Title: Engineering Nanomaterials for the Control of Enzyme Function

Project Description: Enzymes are biological machines that modulate chemical reactions, often crucial to cellular health and metabolism. Both the increase and decrease in function of these proteins are main causes of many known disease processes such as pancreatitis, glycogen storage disease and tumor metastasis. While current treatments often involve extensive screening for small molecule drugs targeting specific proteins, we propose a system for the rational design of functional protein modulators based on single-walled carbon nanotubes (SWCNTs).

One area of Prof. Strano’s laboratory focuses on the engineering SWCNTs as specific biosensors for reactive species, small molecules and proteins. We have discovered a system coined corona phase molecular recognition (CoPhMoRe) where analytes can be specifically identified using its interactions with the external surface of a nanomaterial. This work will extend the technology of CoPhMoRe toward the targeted functional control of biological activity.

As a student on this project, you will be exposed to a very diverse and interdisciplinary research project and lab. You will have the opportunity to learn many different areas of research ranging from synthesis and characterization of our bionanosensors, study of enzyme activity and structure, testing of sensitivity and specificity of the SWCNTs, and potential work with cell culture.  Students will also have the opportunity to learn characterization techniques such as fluorescence spectroscopy, absorption spectroscopy, Raman spectroscopy, circular dichroism and isothermal calorimetry.

Prerequisites: Students with plan for year-long or longer research commitment with interest in biology, chemistry, bioengineering, or nanomaterials. Applications will be considered until 9/15/18.

Relevant URL: srg.mit.edu

Contact: Xun Gong, MD, PhD (xungong@mit.edu)


8/29/18

Term UROP is offered: Fall

UROP Department, Lab or Center: Edgerton Center

MIT Faculty Supervisor Name: Dr. Jim Bales

Project Title: Programing a Stroboscopic Display

Project Description: We have a display that uses strobing LEDs to animate the motion  of falling droplets. (It is a color version of the displays on the 4th floor of the infinite corridor.) We need someone with some embedding programing skill to create a controller to replace our existing analog electronics and explore options for the User Interface. We would consider a dedicated student who wants to learn embedded programming for this position.

Prerequisites:

  • Preferred: Experience with simple embedded programing (counters)
  • Minimum: Strong interest in learning embedded programing.

Contact: Dr. Jim Bales (bales@mit.edu)


8/28/18

Term: Fall/IAP

UROP Department, Lab or Center: Chemical Engineering (Course 10)

MIT Faculty Supervisor Name: Daniel Anderson and Robert Langer

Project Title: Glucose Responsive Materials for Self Regulated Insulin Delivery

Project Description: Many diabetic patients must continually monitor their blood sugar and self-administer multiple daily doses of exogenous insulin to combat hyperglycemia. To reduce this patient burden, limit the occurrence of hypoglycemic events, and better mimic native insulin activity, therapies which can self-regulate insulin delivery are an attractive option.  Existing technologies, however, are typically insensitive to glucose changes at physiologically relevant concentrations and do not respond on therapeutically relevant timescales. This work addresses these limitations by developing new technologies combined with novel in vivo characterization strategies to create a translatable therapy for diabetic patients. Day-to-day work includes polymer synthesis, nanoparticle fabrication, hydrogel formulation, degradation studies, insulin release studies, and various characterization techniques.

Prerequisites:

  • Some wet lab experience preferred
  • Working knowledge of organic chemistry preferred
  • Open-mindedness and willingness to learn new techniques required

Contact: Interested candidates should email their resumes to Lisa Volpatti (volpatti@mit.edu)


8/28/18

Term: Fall/IAP

UROP Department, Lab or Center: Whitehead Institute for Biomedical Research (WI)

MIT Faculty Supervisor Name: Kristin Knouse

Project Title: Dissecting and engineering reversible cell cycle states

Project Description: The Knouse Lab harnesses the incredible genetic tractability and regenerative capacity of the mouse liver to investigate the reversible cell cycle state known as quiescence and reveal novel approaches for regenerative medicine. We are currently interested in understanding the mechanisms underlying the reversibility of the quiescent state and how this state is distinct from terminal differentiation—why a hepatocyte has the capacity to divide again while a cardiomyocyte or neuron cannot. Our lab employs a variety of genetic and bioengineering approaches directly within the mouse. 

We are eager to have undergraduate students join us in these efforts! Students would initially be teamed up with other lab members to learn and assist with techniques such as mouse colony maintenance, mouse surgeries, tissue processing, and cell isolation with the ultimate goal of having their own independent projects.

Prerequisites:

  • Prior research experience in cell, molecular, or organismal biology preferred but not required
  • Experience or willingness to work with mice
  • Preference will be given to students who are willing to work in the lab for multiple semesters and full-time through the summer

Relevant URL: knouselab.org

Contact: Kristin Knouse (knouse@wi.mit.edu)


8/28/18

Term: Fall

UROP Department, Lab or Center: Chemical Engineering (Course 10)

MIT Faculty Supervisor Name: Alan T. Hatton

Project Title: Carbon dioxide capture using a novel electrochemical-based process

Project Description: With the increasing evidence of global warming and its correlation to carbon dioxide (CO2) emission, developing cost-effective, large-scale and efficient CO2 capture technologies is critical. Recently, we demonstrated a CO2 capture system based on an electrochemically-mediated amine regeneration (EMAR) that enables reductions in the energy and capital investment in comparison to traditional thermal swing amine scrubbing technology. An EMAR cell consists of two metallic electrodes (e.g., copper plates), an amine absorbent, and a metal salt. Various variations of EMAR are under investigation and the prospective student will investigate different

amines and metal salts to eventually find the best chemistry to run and operate the EMAR cell. Two key electrochemical-based tools to investigate different chemistries are cyclic voltammetry and electrochemical impedance spectroscopy. The student will be trained by a postdoctoral associate and doctoral student mentors to be able to perform these measurements. Interested candidates should email rahimi@mit.edu with a brief explanation of why they are interested in this project and describe any relevant previous experience.

Prerequisites: Prior experience in a research laboratory is not required but is preferred.

Relevant URL: http://hattongroup.mit.edu/

Contact: Mim Rahimi (rahimi@mit.edu)


8/24/18

Term: Fall/IAP

UROP Department, Lab or Center: Sloan School of Management (Course 15)

MIT Faculty Supervisor Name: Stuart Madnick

Project Title: Cyber Analysis to Improve Operational Response to a Cyber Attacks on Smart Grids

Project Description: Cyber threats are among top issues keeping energy leaders awake at night in Europe and North America. However, the challenges including the differences between utility operation and cybersecurity operation, the communication, and the complex system make it difficult to effectively respond to emerging cyber attack to smart grids. Without preparing operators for potential cyber attacks, the error response can even make it a cascaded cyber disaster.

The goal of this project is to assist the EDS operator’s response to a cyber attack and to improve the cybersecurity resilience. By using the developed analysis model, the related documents and the cyber attack incidents, we will work together to develop a system which is able to: 1) transform guidelines into effective, actionable activities for operators; 2) identify cascading cyber incidents; 3) recommend mitigation procedures for operators.

Prerequisites: Required skills include attention to details, critical thinking, as well as excellent reading, writing, and communication skills. Programming skills (python and front end developing) are essential. Familiarity with STAMP model, smart grid system is a huge plus. Familiarity with cybersecurity is a plus but not required. We are particularly interested in working with motivated and organized students who are committed to doing research.

Relevant URL: https://cams.mit.edu/

Contact: Keman Huang (keman@mit.edu)


8/27/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Guoping Feng

Project Title: Dissecting the role of thalamic neural circuits in learning and memory

Project Description: Learning and memory are essential functions of the brain and are critical for everyday life. While it has been demonstrated that the hippocampus, amygdala, and several cortical regions play a critical role in memory formation, the contributions of thalamic neural circuits remain unknown. In this project, there are three aims/experiments, which will help enhance our understanding of thalamic circuits in learning and memory: (a) Using genome engineering (via CRISPR/Cas9), we will develop novel mouse models that permit the selective manipulation of individual thalamic circuits; (b) Using circuit-tracing and viral injections into the mouse brain, we will map the input-output architecture of sub-nuclei within the thalamus; and (c) Using in vivo neural activity manipulations (via optogenetics) and recordings (via GCaMP imaging), we will uncover the functional role of thalamic neural circuits during mouse behavioral paradigms and further investigate how these circuits are disrupted in mouse models of human disorders including autism, Alzheimer’s disease, and intellectual disability. We are looking to fill 1-2 UROP positions for these experiments immediately.

Prerequisites: The ideal candidate will be excited to join a dynamic research team in the neuroscience field and be motivated to develop molecular/circuit-tracing skills in an efficient manner. Experience with mouse surgeries, behavior, or molecular biology is a plus.

Relevant URL: http://fenglaboratory.org/

Contact: Dheeraj Roy (droy@broadinstitute.org)


8/27/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Mriganka Sur

Project Title: Uncovering the brain mechanisms that control locomotion

Project Description: How does the brain voluntarily select, generate and control dynamical motor behavior?  What are the mechanisms by which the brain timely combines different information to achieve precise motor control?  As a gateway to answering these questions, we are studying the control of locomotion in mice.

Mice are trained to play a running-based virtual-reality game. Through a combination of anatomical tracings, optical and electrophysiological recordings of neuronal activity, optogenetics manipulations and computational/mathematical techniques, we are dissecting the circuitry and the dynamics overlaying this circuitry that allow mice to execute patterns of running, stopping and waiting.

We are looking for a highly motivated undergraduate who would be interested in taking part in this project.  As a UROP, depending on your interest, you will be assisting in:

  • Histology and confocal imaging (e.g., slicing, mounting, and imaging microscope slides)
  • Animal handling, behavioral training and equipment development
  • Performing imaging/recording experiments
  • Computational analysis of behavioral and neuronal data

Prerequisites: Students from other disciplines, especially engineering, are very encouraged to apply.  A lack of background in neuroscience can be compensated by great enthusiasm and an eagerness to learn!  Priority will be given to first-time UROPs who are looking for a long-term commitment.

Contact: Elie Adam (eadam@mit.edu)


8/27/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Nicholas Feng

Project Title: Ultrasonic Levitation with Highly Tunable Phased Arrays

Project Description: Liquids handling or micropipetting systems bear central stage in biological research while demanding stringent requirements to be RNase-free. Our lab is pursuing the use of ultrasonic phased arrays to make some of these work more efficient by doing away with manual labor and instead levitating and dispensing liquids using invisible acoustic waves.

We have currently developed an acoustic phased array which is digitally tunable in real-time and are looking for students to play with this device. The project plan is to use reinforcement learning to determine the optimal strategy to hover, move, eject, disperse, or aggregate tiny droplets using ultrasonic phased arrays with array elements tunable by phase, frequency and amplitude.

Prerequisities: The student must have written at least 5,000 lines of code in any language, or aware of systems engineering concepts to be able to write scalable code. Familiarity with reinforcement learning, such as in the use of libraries such as Keras, TensorFlow, PyTorch, etc… will be very useful. The work will involve database handling, so experience with either HDF5, Pandas DataFrames, or even CSV and SQL, will be helpful.

Relevant URL: http://web.mit.edu/nanophotonics/

Contact: Zheng Jie Tan (zjt@mit.edu) and Chu Ma (machu@mit.edu)


8/27/18

Term: Fall

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Nicholas Fang

Project Title: Advanced Investment Casting with High Resolution 3D-Printed Patterns

Project Description: Investment casting allows metal parts to be created from wax or plastic sacrificial patterns. This is a scalable low cost technique with a resolution and surface smoothness better than existing direct metal 3D printing technologies. Our lab has developed equipment to perform investment casting using 50µm high resolution parts printed in-house by our Autodesk Ember printer.

There are many unexplored areas where on-demand metal parts of arbitrary geometries can come in handy. We are currently seeking applicants to help with exploring the uses of casted metal parts for optical applications, such as with functionalized opto-mechanical mounts or directly as reflective optics. This work involves CAD work of custom-designed parts, their printing and eventually casting. The job scope is flexible because all the process steps are carried out in our lab with either open-source or custom-developed hardware to easily test new ideas.

Prerequisites: Open to all engineering majors of any year. Strong interest or experience in any of following is preferred: programming (we’re working primarily with Python), image processing, optimization, optical systems, CAD, 3D printing, systems design or machining will be helpful.

Relevant URL: http://web.mit.edu/nanophotonics/

Contact: Zheng Jie Tan (zjt@mit.edu)


8/27/18

Term:Fall/IAP

UROP Department, Lab or Center: Sloan School of Management (Course 15)

MIT Faculty Supervisor Name: Y. Karen Zheng

Project Title: Data-Driven Design for e-Agricultural Markets to Improve Market Efficiency and Farmer Welfare

Project Description: Want to improve livelihoods of farmers in India through your work? Our goal in this research is to employ a data-driven approach combining machine learning, mathematical modeling, and field experiments to optimize the design of India’s online agricultural platforms. It is reported that Indian farmers earn as little as 30% of the value of their products, compared to 50% in the United States. India’s regulated markets and the resulting market structure have led to poor outcomes for farmers because of barriers to entry, information asymmetry and non-transparent price setting processes. In order to tackle such inefficiencies, the government has launched an online platform that aims to connect markets all over the country. We seek a UROP to assist us in an empirical study that quantifies the effect of this new platform on market outcomes.

Tasks for UROP:

  • A) Create scripts for web scraping of data related to market prices, characteristics etc.
  • B) Collect and process data, and conduct preliminary analysis involving machine learning techniques to draw valuable insights from the data

Prerequisites:

  • (1) Familiar with programming, particularly web scraping, and creating structured datasets/database.
  • (2) Experience in machine learning tools.
  • (3) Minimum 10 hours per week.
  • (4) For credit or for pay ($15/hour).

Relevant URL: https://goo.gl/CS2b7J

Contact: Somya Singhvi (ssinghvi@mit.edu)


8/27/18

Term UROP is offered: Fall

UROP Department, Lab or Center: Biology (Course 7)

MIT Faculty Supervisor Name: Domitilla Del Vecchio

Project Title: Desing and Build Robust Biomolecular Circuits

Project Description: The field of synthetic biology allows researchers to engineer life. We can program cells to create bio-fuels from renewable energy sources, detect toxins, battle disease and bring us closer towards making space exploration cost-effective. However, like any other maturing field, there are several challenges that must be addressed before unlocking its full potential.

A key issue facing synthetic biology is characterizing how natural cellular resources (which power our bio-molecular circuits) are shared within the cell. When these resources become limiting  the performance of our circuits is harmed. In this project we attempt to build biomolecular controllers to mitigate the negative affects of resource sharing using fundamental principles in control theory.

Role: Biomolecular circuit design, assembly and testing.

If you are interested in being involved in this project, please contact Carlos Barajas (carlobar@mit.edu) with your resume and any question you might have.

Prerequisites:

  • Basic bio lab experienced  (7.02)
  • Cloning experience
  • Plasmid design ( using Benchling or Snapgene)
  • Basic knowledge of ordinary differential equations useful but not required
  • Some Matlab (not required, but useful)

Relevant URL: http://scripts.mit.edu/~ddv/index.php

Contact: Carlos Barajas (carlobar@mit.edu)


8/24/18 

Term: Fall/IAP

UROP Department, Lab or Center: Linguistics and Philosophy (Course 24)

MIT Faculty Supervisor Name: Martin Hackl

Project Title: Child Language Development Research

Project Description: We investigate the nature of human language, by studying immature language in the child (the development of language). The research interweaves current linguistic theory and empirical work. The current research areas include quantified statements, focus operators, and presuppositions. Your work will involve (i) running experiments with children (mainly 3-6 years old), (ii) data entering and assisting with interpretation, (iii) interacting with day cares and parents for consent. It might also involve (iv) assistance in experimental design and preparation of experimental materials.

The ideal UROP will be enthusiastic about engaging with children, interested in linguistics and language development, and looking for a chance to learn new skills. The UROP's main goals will be: engagement with cutting edge theoretical developments in language acquisition and acquiring hands-on experience with behavioral research with children.

Please contact us with a resume or CV. Wellesley Students are welcome and encouraged to apply.

Prerequisites: There are no pre-requisites for this UROP assignment. Having taken 24.900 is preferred but not required. Given that the work is mainly about interaction with children and keeping them engaged in the experiments, you will have to be very good at playing with kids in a structured way. You must also have large chunks of time available during weekdays in either mornings or afternoons, in order to run experiments. 

Relevant URL: http://web.mit.edu/lacqlab/home.html

Contact: Leo Rosenstein (leaena@mit.edu)


8/24/18

Term: Fall/IAP

UROP Department, Lab or Center: Earth, Atmospheric, and Planetary Sciences (Course 12)

MIT Faculty Supervisor Name: Ruben Juanes

Project Title: Machine Learning and Computer Simulation of Earthquakes

Project Description: Understanding and predicting earthquakes remain a fundamental challenge that continues to elicit fascination from the scientific community and society alike. While much of the understanding has come from field observations, research over the past few decades has contributed to advances in the cause of triggered seismicity, and the formulation of constitutive laws of frictional weakening at geologic faults that are capable of reproducing the statistics of tectonic earthquakes.

The goal of the present project is to combine advanced computational modeling of coupled flow and geomechanics that simulate dynamic rupture of geologic faults with data streams of recorded seismicity. The use of machine learning tools will enable the parsing of phenomenally large datasets of measurements at seismic stations into a set of attributes that encode the essential features of an earthquake signal. If successful, this will permit "training” computer simulations to, eventually, arrive at predictive physical models of earthquake occurrence—a landmark result in geoscience.

In this project, you will work directly with a postdoc in the development of recent computational geophysical models in Python-TensorFlow (https://www.tensorflow.org/), and the application of these tools to understanding tectonic and induced earthquakes. We anticipate that the work will lead to presentations in international conferences and publications in top scientific journals.

Prerequisites: Good knowledge of computer programming in Python is a must. 

Contact: Ehsan Haghighat (ehsanh@mit.edu)


8/24/18

Term: Fall/IAP

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: John Lienhard

Project Title: Chemical-free Membrane Cleaning in Desalination & Water Purification 

Project Description: Surface fouling is one of the leading causes of inefficiency in marine vehicles such as ships, reverse osmosis (RO) processes and failure of biomedical devices. In RO processes, fouling of the membrane is one of the largest contributors to downtime and energy waste, costing the industry billions in losses. Current state-of-the-art involves the use of chemicals which increases the cost of water production and have an adverse effect on the environment.

Our eventual goal is to propose a method for in situ removal of foulant from the RO membranes, which has great bearings on advancing the goal of having a sustainable and efficient water supply.

Here, we explore the use of mechanical vibration to solve the issue of RO membrane fouling. The experiment is based on a flow cell that mimics the flow and fouling conditions in an RO module. Pressure variation is imposed to cause vibration in the RO membranes. Water production flux will be monitored to evaluate the effectiveness of vibration cleaning.

The UROP(s) will be performing some of the experiments to verify the optimal conditions to remove the foulants from the surface. This opportunity is a great way to learn about the RO process and membrane technology while also gaining experience in working with pneumatic, mechanical and instrumentation components of an experimental setup.

Prerequisites: Enthusiasm is greatly appreciated! You are responsible for direct funding application (deadline Sept 20) or opt for credits. No prior experience is required, although candidates who have taken classes on fluid mechanics, structure mechanics or dynamics would be would be preferred.  Experience with graphic design (e.g. Adobe Illustrator) to prepare visuals is a plus.

Due to the nature of the experiment, the only requirement is that the UROP has to stay in the lab for blocks of 4 hours (most of it is passive waiting time). The workday of the UROP is flexible.

Contact: Omar Labban (olabban@mit.edu)


8/24/18

Term: Fall/IAP

UROP Department, Lab or Center: The MIT Energy Initiative (MITEI)

MIT Faculty Supervisor Name: Francis O'Sullivan

Project Title: Machine learning and interactive web application for unconventional oil and gas production and economics

Project Description: We are combining machine learning/data science with interdisciplinary domain knowledge (e.g. geology, fluid flow dynamics, extraction technology) to predict the amount and extraction cost of oil and gas in unconventional resource basins. Production from these resources has advanced rapidly in the past decade, upending commodity markets and boosting US oil and gas production to record levels. However, there is still significant uncertainty about the productivity and economics of the resource in the future as technology continues to evolve.  

Our aim is to use cutting edge statistical modeling to reduce this uncertainty and inform planning and investment decisions by developing models of the production and economics across large unconventional resource basins spanning thousands of wells. We are pioneers in this space and have received media attention for the research (see interview from last fall).

This research opportunity includes working with and improving existing machine learning and economic models we have developed as well as developing new approaches. Additionally, this position will involve expanding on the functionality of an interactive web application we have developed for exploring well economics (shalestats.com). This will consist of developing additional data visualization tools and interactive dimensions to the website as well as improving the website interface, design, and architecture. Significant industry attention is already on this website so this is a great opportunity to work on something with great exposure.

Prerequisites: Desired skills include proficiency in a high-level programming language (e.g. Python or R) and experience with web programming (e.g. Javascript). If interested, please send CV/resume and in your email describe any relevant experience you have and why you think you are a good applicant.

Relevant URL: shalestats.com

Contact: Justin Montgomery (jbm@mit.edu)


8/24/18

Term: Fall/IAP

UROP Department, Lab or Center: Chemical Engineering (Course 10)

MIT Faculty Supervisor Name: Michael S. Strano

Project Title: Nanoscale biosensors for in vivo monitoring of drug delivery, treatments, and response for cancer, diabetes, and sepsis

Project Description: Prof. Strano’s laboratory focuses on the development of nanoscale biosensors and materials for a wide array of applications.  A growing area of our research is the development of nano-biosensors for medical applications in particular in cancer, diabetes, bacterial sepsis, and hematology  to probe biologically relevant analytes in vivo and in real-time. Recently, we have developed a series of near-infrared (nIR) fluorescent probes for sensing reactive oxygen species, reactive nitrogen species, chemotherapeutic drugs, insulin, and are looking to develop new sensors. 

Our lab has customized these nanosensors for a wide range of biomedical analytes such as saccharides, dopamine and neurotransmitters, glucose, insulin, and cortisol.  Our lab is pursuing a number of applications in cancer research to study chemotherapeutic drug delivery, tumor development, progression, and response to therapies.  This includes identification of potential cancer biomarkers, in vitro validation studies (cell cultures and 3D models), and in vivo studies in orthotopic xenograft animal models.  This new nanoscale sensor-imaging platform will allow for monitoring biomolecular changes at earlier time points following chemotherapy, radiation therapy, or immunotherapies, clinicians will be able to more promptly adapt the patient’s treatment strategy depending on the tumor response.  For the diabetes, we are interested in continuing to develop our insulin sensors to determine and tune its sensitivity and specificity as we transition the validation of the sensor into in vitro and in vivo.  

For bacterial sepsis, we are interested in developing new nanoscale biosensors for studying drug delivery and drug susceptibilities.  For hematology, we are interested in developing new nanoscale biosensors for serologic tests.  We also work on the development of in vitro 3D tumor tissue models and the development of hydrogel (polymer chemistry) constructs to study our sensors in vitro initially before transitioning to in vivo.  We are also working on computational models for studying the delivery and diffusion of both drugs into human tissue for cancer and diabetes.

As a student on this project, you will be exposed to a very diverse and interdisciplinary research project and lab. You will have the opportunity to learn many different areas of research ranging from synthesis and characterization of our bionanosensors, to development and testing of biocompatible form-factors (hydrogels) to encapsulate our bionanosensors, testing the sensitivity and specificity of the sensors to the analyte of interest, to testing of sensor response in solution phase, in cell cultures or 3D tumor models, and ultimately in xenograft orthotopic cancer animal models.  Students will also have the opportunity to learn several optical techniques such as fluorescence spectroscopy, absorption spectroscopy, and Raman spectroscopy.  Students may also choose to be involved in the design and development of optical systems (free space and fiber optic) including optical design, hardware instrumentation, and software instrumentation.

Student's specific project will be tailored to the student's particular interest, research needs of our lab, and student's previous experience.

Prerequisites: Students interested in year long or longer research opportunity with interest in biology, chemistry, bioengineering, materials science, mechanical engineering, chemical engineering, physics, or optics. Multiple student positions are available for these projects.

Relevant URL: srg.mit.edu | freddynguyen.org

Contact: Freddy Nguyen, MD, PhD (freddytn@mit.edu)


8/24/18

Term: Fall/IAP

UROP Department, Lab or Center: Chemistry (Course 5)

MIT Faculty Supervisor Name: Daniel Anderson

Project Title: Synthesis and indentification of glucose responsive materials drug delivery

Project Description: Type 1 diabetes (T1D), also known as juvenile diabetes, is a growing health crisis all over the world with the total annual global costs amounting to US$500 billion including the treatment related to its complications. Self-administration of insulin injections, which is critical in maintaining a healthy normal blood glucose level, is an important component in managing diabetes. As the traditional insulin therapy is expensive, painful and inconvenient. This project will synthesis and evaluate the next generation glucose-responsive chemosensors with physiologically relevant glucose-responsiveness. It involves interesting and challenging organic synthesis as well as molecular biology

Prerequisites: We seek students with a strong background and hands on experience in organic chemistry and molecular biology.

Relevant URL: http://anderson-lab.mit.edu/

Contact: Chandra Bhattacharya (cbhattac@mit.edu)


8/23/18

Term: Fall/IAP

UROP Department, Lab or Center:  - Interdisciplinary Labs and Centers -

MIT Faculty Supervisor Name: Professor Stuart Madnick

Project Title: Interdisciplinary research to enhance the cyber security resiliency

Project Description: Cyber security plays an important role for the digital society. Without considering and managing risks in cyber security, managers put their entire organization in jeopardy. However, cybersecurity requires more than just the latest technology.  Research has shown that the majority of cyber breaches occur because a person did something wrong either by accident or maliciously.

Cybersecurity at MIT Sloan (CAMS) fills a critical need for leaders and managers of cybersecurity. Our research focuses on managerial, strategic and organizational topics.  Our current projects fall into 5 different research stream including cybersecurity culture, IoT and end-point security, Cyber risk management, Industrial control systems (ICS), and Understanding the business of the dark web.  We seek undergraduate researchers interested in creating the latest thinking about cybersecurity.

We have several projects for interested UROP students.  Some examples:

  1. Cyber security culture project.  This project asks how leaders can shape the beliefs, values, and attitudes of their organizations to align with overall cyber security goals. The UROP student will work together with our research team to collect and analysis survey data, assist with interviews, and draft a report of findings based on the empirical study.
  2. Cybersecurity impact on international trade. This project seeks to understand how the cybersecurity concerns impact the international trade and how governments and businesses might react to such concerns. We have been focusing on the digital services and digital supply chain and have come up with several models of impact. The UROP student will work with the team to enrich the case dataset, and assist with related interviews and document the findings.

We have other cybersecurity research opportunities so please contact us if this area is of interest.

Prerequisites: Required skills include attention to details, critical thinking, as well as excellent reading, writing, and communication skills.  Students who are self-starters and like to take the lead to get projects accomplished are especially needed.  Background in political science, organizational design, data analysis, or quantitative analysis is a huge plus. Familiarity with cybersecurity is a helpful but not required—you will learn on the job. We are particularly interested in working with motivated and organized students who are committed to doing research.

Learning opportunities: Overall, these projects can enhance your critical thinking, and explore the interdisciplinary research in cybersecurity domain, and prepare you with hands-on experience in cybersecurity, cybersecurity management and international trade.  You will also get experience with presentations and business writing.  Selected candidate(s) can join the project immediately or begin since the fall semester.

Relevant URL: You will be working with Cybersecurity at MIT Sloan (https://cams.mit.edu).

Contact: Please email Dr. Keman Huang (keman@mit.edu) with 1) your CV, and 2) a brief description of your interest in projects mentioned


8/23/18

Term: Fall

UROP Department, Lab or Center: Center for Transportation & Logistics (CTL)

MIT Faculty Supervisor Name: Jarrod Goentzel

Project Title: Building a reliable disaster portfolio through text-mining

Project Description: Effective analysis of logistics capacity – particularly the deployment of stockpiles and consignment inventory to meet human needs in the aftermath of a disaster – is critical in preparedness efforts for disaster response. Building on stochastic optimization models previously developed by the researchers of the Humanitarian Supply Chain Lab and utilized by the Federal Emergency Management Agency (FEMA) to analyze logistics capacity and inform disaster preparedness decisions, this project seeks to improve the information on disaster scenarios.

This is particularly important because the disaster scenarios fed into the model determine the accuracy of recommendations from the model. However, to date, reliable information on the number of people affected by disasters is not available in a structured way and even large governmental organizations are lacking accurate information for their planning processes.

The candidate will provide support developing a method to collect and recombine publicly available data in innovative ways to create reliable disaster scenarios. Previous experience with Python or R and interest in semantic analysis/ text mining will be very helpful. Working alongside researchers at the MIT Humanitarian Response Lab, the candidate will help improve the accuracy of model outputs. These outputs are directly used by emergency response organizations to improve their response capacity and better serve disaster survivors.

Depending on the interest and skills of applicants, this position may include a focus on:

  • Disaster data collection from FEMA, NOAA/NWS, and CRED EM-DAT
  • Acquisition of additional information, e.g. newspapers, and creating a data base
  • Text mining and semantic analysis of disaster data and additional information
  • Running a two-stage SLP model with improved disaster scenarios and evaluate improvements

For more information, email Alexander Rothkopf at rothkopf@mit.edu.

Prerequisites:

  • Experience in Python or R is very helpful
  • Prior knowledge in text-mining/semantic analysis or machine learning methods is helpful

Contact: Alexander Rothkopf (rothkopf@mit.edu)


8/23/18

Term: Fall/IAP

UROP Department, Lab or Center: Materials Science and Engineering (Course 3)

MIT Faculty Supervisor Name: Jeffrey C Grossman

Project Title: Development of spectroscopic methods to evaluate chemical composition of early life organic carbon for space exploration

Project Description: We are seeking a Fall/IAP UROP to help an ongoing effort to develop characterization methods based on Raman spectroscopy aimed at rapid evaluation of the chemical composition of ancient organic matter, that can be used to estimate age, geological metamorphism, degradation of biological material of the early Earthly life and beyond. The developed methods will allow for potential analysis in future Mars geobiology missions, as well as to rapidly assess the presence of biosignatures remaining in ancient organic matter.

The project will involve: 1. Raman spectroscopy data collection for a suite of well characterized carbonaceous materials. 2. Establish correlations with chemical parameters based on the ongoing work, both through statistical analysis and machine learning methods. 3. Test and validate such correlations with a broad range of organic matter relevant to the ultimate task of identifying preserved biosignatures in early life.

The project is directed and coordinated by Dr. Nicola Ferralis in the Department of Materials Science and Engineering (DMSE, Course 3), in collaboration with the Geobiology group in Earth, Atmospheric, and Planetary Sciences (EAPS) run by Prof. Roger E. Summons.

Prerequisites: The successful candidate will work with DMSE and EAPS researchers to collect, process Raman data and develop basic statistical algorithms and related machine learning models. Basic Chemistry and Physics of Materials knowledge is required. Previous experience with Raman spectroscopy is highly desired. Experience with Python is not required but useful.

Contact: Nicola Ferralis (ferralis@mit.edu)


8/23/18

Term: Fall/IAP

UROP Department, Lab or Center: Physics (Course 8)

MIT Faculty Supervisor Name: Crossfield

Project Title: The Final Frontier: Isotope Ratios in Dwarf Stars

Project Description: Astronomers now routinely measure the bulk properties of stars -- temperatures, radii, masses, and chemical abundances.  Perhaps the final frontier in observational stellar astronomy is the determination of *isotopic* abundances -- the focus of this UROP. Tasks include: searching data archives for applicable archival spectroscopy; downloading & reducing these data; preparing for and/or conducting observations; and analyzing extracted spectra to measure isotopic ratios.

Prerequisites: Basic astrophysical knowledge (e.g 8.282, 8.284, or equivalent) and basic programming (Python preferred).

Contact: Ian Crossfield (iancross@mit.edu)


8/22/18

Term: Fall/IAP

UROP Department, Lab or Center: Sloan School of Management (Course 15)

MIT Faculty Supervisor Name: Michael Siegel

Project Title: Learning from the Attack Model: Better Defense using Phishing as a Service

Project Description: Cyber attacks are increasingly menacing businesses. To better understand the cyber attack business we conducted an extensive analysis of the services used by cybercrime businesses. Understanding the specialization, commercialization, and cooperation for cyber attacks helped us to identify twenty four key value-added activities and their relations. These activities are being offered “as a service” for use in a cyber attack. This framework helps to understand the cybercriminal service ecosystem and hacking innovations. Using this result, this research plans to develop one or more of these services for use by the offense. Specifically we will examine the “phishing” capabilities in various attack offering and develop an approach that can be used to counterattack these services.

In this project, we intend to study the attacker’s approaches in phishing services and develop tools and techniques to help to build more realistic tools for protecting organizations. We will develop research including but not limited to:

  • 1) Analyze offensive (attack) and defensive phishing tools and techniques; 
  • 2) Examine existing phishing Saas and its uses for creating a better defense. 
  • 3) Develop a proof of concept of the developed approach.

Learning opportunities: Overall, this project can enhance your critical thinking, simulation modeling, data analysis and artificial intelligence skills, and prepare you with hands-on experience in cybersecurity, simulation, and decision-making sciences. Selected candidate(s) can join the project immediately or begin since the spring semester.

Prerequisites: Required skills include attention to details, critical thinking, as well as excellent reading, writing, and communication skills. Programming skills (python, selenium, tor, NLP) are essential. Familiarity with cybersecurity and simulation modeling techniques is a plus but not required. We are particularly interested in working with motivated and organized students who are committed to doing research.

Relevant URL: You will be working with Cybersecurity at MIT Sloan (http://cams.mit.edu).

Contact Name: Dr. Keman Huang (keman@mit.edu)


8/22/18

Term: Fall/IAP

UROP Department, Lab or Center: Comparative Media Studies (CMS)

MIT Faculty Supervisor Name: Ian Condry

Project Title: Live music listings app & website development, team project

Project Description: We are a team developing a mobile app and website to provide listings for live music events in the Boston area, with the aim of expanding to other cities as well.  During this UROP, you will work with a professor of Global Studies and Languages (GSL) and Comparative Media Studies (CMS/W) in a structured and supportive work environment.  The project now has a working version of the app, but one that still requires substantial ongoing development.  The project involves various aspects, including data scraping, database management, adding app features, testing with users..  Additionally, we are planning to start development of a website this semester. We expect 5-10 hours per week if possible, though we have some flexibility too.  UROP may taken for pay (direct funding) or course credit.

Prerequisites: We seek people with an interest in understanding the dynamics of live music local communities, who also have interest in learning about text extraction tools, database management, and app & website creation in structured and supportive group work environment.  Computer science background in Python, Javascript, ReactNative mobile app development, web scraping, SQL, or HTML & WordPress are a plus, but we also welcome people who are willing to learn. We also have an opening for an analyst to conduct ethnographic & industry/business research.

Contact: Ian Condry (condry@mit.edu)


8/22/18

Term: Fall

UROP Department, Lab or Center: Political Science (Course 17)

MIT Faculty Supervisor Name: Charles Stewart III

Project Title: GIS/Electoral Boundaries Initiatives in Election Science

Project Description: The need for science and transparency in the analysis of elections is an increasingly important part of our democracy. As the MIT Election and Data Science Lab (MEDSL) continues to grow we are are working towards the goal of becoming the foremost clearinghouse for election science data—including data related to GIS and redistricting efforts. Although much data exists, it is often disorganized and not in easily-analyzed formats. This UROP is an opportunity to be part of improving access to data and contributing to election science research.

As a UROP working on this project you will:

  • Collect and organize election science data relating to geographic boundaries
  • Demonstrate your GIS skills and expand your understanding of electoral boundaries in the US
  • Present interesting research ideas and findings to the larger group
  • Learn additional data management and statistical programming skills
  • Contribute to ongoing MEDSL research projects
  • Work towards answering your own research questions related to election science
  • Participate in weekly lab meetings

Prerequisites: GIS experience is required. The UROP should also be familiar with data management in formats such as comma/text delimited and/or Excel-type spreadsheets. Additional programming or statistical software skills (e.g., C/C++, MATLAB, Python, R, Stata) are desired. Please indicate your level of familiarity with GIS, data collection and management, econometrics, statistical programming, and web (data) scraping when you apply. We welcome applications from students at both MIT and Wellesley. The UROP can be for credit or pay.

Relevant URL: electionlab.mit.edu

Contact: Dr. Cameron Wimpy (wimpy@mit.edu)


8/22/18

Term: Fall/IAP

UROP Department, Lab or Center: Lincoln Labs

MIT Faculty Supervisor: Timothy Leek

Project Title: Automated Rehosting of Embedded Devices

Project Description: Our lab is developing technology to automate the ad-hoc and manual process of “rehosting” – configuring a specialized device (ex. a wireless router) to run in a general purpose emulator (ex. PANDA). Rehosting enables dynamic analysis, a fundamental capability for vulnerability research. Developing repeatable and reliable techniques for rehosting is critical to improving the security of “Internet of Things” (IoT) devices.

We are looking for a student to help improve our rehosting tooling and methodology. Given the broad problem space, there are opportunities for novel work on several fronts – VM introspection, peripheral identification, peripheral modeling and emulation, and algorithm design. Potential tasks may include any of the following, dependent on student background and/or preference:

  1. Reverse engineer a specific peripheral and write a PANDA plugin to emulate it
  2. Develop introspection tooling to automate the collection of peripheral information by hooking kernel functions
  3. Evaluate and implement algorithms and heuristics for iterative peripheral discovery
  4. Develop novel methods to collect “traces” (artifacts of correct sequential execution) from target hardware

You will work alongside a team of cross-disciplinary researchers at MIT Lincoln Laboratory. At least one full-time staff member will be responsible for helping guide and support your project.

Pre-requisites: Prior exposure to operating system and virtualization concepts, ability to program in C and Python. Experience with system emulation (ex. QEMU) or embedded systems (ex. microcontrollers) is a plus. Above all, willingness to “deep dive” into challenging technical work!

Contact info: Interested students should contact Tim Leek and Tiemoko Ballo (tleek@ll.mit.edu, Tiemoko.Ballo@ll.mit.edu).


8/22/18

Term: Fall

UROP Department, Lab or Center: Whitehead Institute for Biomedical Research (WI)

MIT Faculty Supervisor Name: Sebastian Lourido

Project Title: Optimization of an EM clustering algorithm for determining RNA structure

Project Description: The project involves optimizing model parameters  and convergence criteria for Expectation Maximization Clustering algorithm that we have applied to determine alternative RNA structures formed from the same underlying sequence. Interest in biology is encouraged but biology background is not necessary.

Prerequisites: Math or math and computer science majors; Juniors or Seniors only.

Relevant URL: www.rouskinlab.com

Contact: Silvi Rouskin (srouskin@wi.mit.edu)


8/22/18

Term: Fall/IAP

UROP Department, Lab or Center: Materials Science and Engineering (Course 3)

MIT Faculty Supervisor Name: Michael Cima

Project Title: Implantable devices for tumor diagnosis and drug therapy

Project Description: The Cima Lab is looking for an undergraduate researcher to participate in the development of novel implantable devices for tumor therapy and diagnosis. Tumors can vary significantly from patient to patient, causing different susceptibility of each to standardized drug regimens. Our devices help guide clinical therapy based on tumor type and susceptibility to up to 20 drugs in a single device. This information allows for tailored therapy, maximizing treatment efficacy and patient outcomes. A student on this project will focus on designing and fabricating the microdevice as well as subsequent tissue processing and data analysis.  An ideal student will be enthusiastic about learning techniques in device design, interested in expanding their general knowledge about translation biomedical devices, and committed to making an impact on the project.

Prerequisites: No experience is required. Training will be provided in all areas. We will give preference to candidates who can commit to working at least 12 hours per week during the academic year. We are offering academic credit for new UROPs. The position is available starting September 2018.

Contact: Khalil Ramadi (kramadi@mit.edu)


8/22/18

Term: Fall/IAP/Spring

UROP Department, Lab or Center: Materials Science and Engineering (Course 3)

MIT Faculty Supervisor Name: Michael Cima

Project Title: Machine learning algorithms for tumor sample image processing

Project Description: : The Cima Lab is looking for an undergraduate researcher to participate in the development of algorithms for intelligent image analysis of tumor samples. Tumors can vary significantly from patient to patient, causing different susceptibility to standardized drug regimens. The Cima lab has developed implantable devices to characterize tumor type and susceptibility to up to 20 different drugs. Treatment efficacy is quantified by image analysis of tumor samples. Extremely precise analytical techniques are critical for accurate assessment of tumor susceptibility to each drug.

This information allows for tailored therapy, maximizing treatment efficacy and patient outcomes. A student on this project will focus on designing and implementing algorithms to quantify effect of drug on different tumors. The ideal student will be enthusiastic about learning techniques in image analysis, applying machine learning protocols to improve analysis, expanding their general knowledge about translational engineering, and committed to making an impact on the project.

Prerequisites: No experience is required. Prior knowledge of MATLAB and general image analysis techniques is preferred. Training will be provided in all areas. We will give preference to candidates who can commit to working at least 12 hours per week during the academic year. We are offering academic credit for new UROPs. The position is available starting September 2018.

Contact: Khalil Ramadi (kramadi@mit.edu)


8/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Civil and Environmental Engineering (Course 1)

MIT Faculty Supervisor Name: Dara Entekhabi

Project Title: Assessing climate vulnerability of West African food security using remote sensing analysis

Project Description: Want to use your coding skills to fight the impacts of climate change? Data on agriculture production in West Africa is scarce, making it difficult to analyze the impacts of climate change on crop yields. Our team is using satellite imagery to estimate historical crop yields and cropped area in the region. We will then use these estimates to determine the relationship between climate and crops, and how this may evolve in the future. The project leverages Google Earth Engine, a cloud-computing platform that makes analytics of earth observation data feasible at larger scales than ever before.

The main task for the UROP is to validate a landcover classification algorithm. We need a student to write a script to download high resolution imagery from Google Earth, visually inspect this imagery, and use it to validate a classifier. Motivated UROPs will also have the opportunity to contribute to the development of algorithms for image segmentation and yield estimation and co-author scientific publications. The UROP will be closely mentored by Postdoctoral Associate Sarah Fletcher.

To apply, please email Sarah Fletcher (sfletch@mit.edu) with: 1) your resume and 2) a brief description of your programming experience. Samples of previous coding projects may be requested. Priority deadline is Monday September 3.

Prerequisites: Candidates should have prior programming experience and an interest in environmental issues. Experience with JavaScript and/or Python preferred.

Prerequisites: Candidates should have prior programming experience and an interest in environmental issues. Experience with JavaScript and/or Python preferred.

Relevant URL: https://jwafs.mit.edu/research/projects/2018/assessing-climate-vulnerability

Contact: Sarah Fletcher (sfletch@mit.edu)


8/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Political Science (Course 17)

MIT Faculty Supervisor Name: Charles Stewart III

Project Title: Data Coding and Dissemination in Election Science

Project Description: The need for science and transparency in the analysis of elections is an increasingly important part of our democracy. As the MIT Election and Data Science Lab (MEDSL) continues to grow we are are working towards the goal of becoming the foremost clearinghouse for election science data. Although much data exists, it is often hard to access and out of date. This UROP is an opportunity to be part of improving access to data and contributing to election science research.

As a UROP working on this project you will:

  • Collect and organize election science data by coding election laws, policies, and state websites
  • Contribute to MEDSL’s election science dissemination efforts
  • Present interesting research ideas and findings to the larger group
  • Learn additional data management and statistical programming skills
  • Contribute to ongoing MEDSL research projects
  • Work towards answering your own research questions related to election science
  • Participate in weekly lab meetings

Prerequisites: You should be familiar with data management in formats such as comma/text delimited and/or Excel-type spreadsheets. You should also be familiar with basic Word processing and web design. Additional programming or statistical software skills (e.g., R, Stata) are desirable but not required. Please indicate your level of familiarity with data collection and management, econometrics, and web design when you apply. Students with experience in elections or the social sciences are strongly encouraged to apply. We welcome applications from students at both MIT and Wellesley. The UROP can be for credit or pay.

Relevant URL: electionlab.mit.edu

Contact: Dr. Cameron Wimpy (wimpy@mit.edu)


8/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Political Science (Course 17)

MIT Faculty Supervisor Name: Charles Stewart III

Project Title: Data Initiatives in Election Science

Project Description: The need for science and transparency in the analysis of elections is an increasingly important part of our democracy. As the MIT Election and Data Science Lab (MEDSL) continues to grow we are are working towards the goal of becoming the foremost clearinghouse for election science data. Although much data exists, it is often disorganized and not in easily-analyzed formats. This UROP is an opportunity to be part of improving access to data and contributing to election science research.

As a UROP working on this project you will:

  • Collect and organize election science data
  • Present interesting research ideas and findings to the larger group
  • Learn additional data management and statistical programming skills
  • Contribute to ongoing MEDSL research projects
  • Work towards answering your own research questions related to election science
  • Participate in weekly lab meetings

Prerequisites: You should be familiar with data management in formats such as comma/text delimited and/or Excel-type spreadsheets. Additional programming or statistical software skills (e.g., C/C++, MATLAB, Python, R, Stata) are desired. Please indicate your level of familiarity with data collection and management, econometrics, statistical programming, and web (data) scraping when you apply. We welcome applications from students at both MIT and Wellesley. The UROP can be for credit or pay.

Relevant URL: electionlab.mit.edu

Contact: Dr. Cameron Wimpy (wimpy@mit.edu)


8/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Health Sciences and Technology (HST)

MIT Faculty Supervisor Name: Hugh Herr

Project Title: Computational Analysis of Neuroimaging Data

Project Description: The MIT Center for Extreme Bionics is looking for students interested in applying their computational skills to neuroimaging. We are performing neuroimaging for patients undergoing a novel surgical paradigm developed for limb amputation. The UROP project will involve analysis of this data set using Linux-based softwares such as FreeSurfer. This opportunity avails  exposure to exciting and state-of-the art neuroprosthetics research.  Please contact shriyas@mit.edu with your CV if interested.

Prerequisites:

  • Experience coding with Linux
  • Interest in neuroanatomy

Relevant URL:

Contact: Shriya Srinivasan: (shriyas@mit.edu)


8/17/18

Term: Fall/IAP

UROP Department, Lab or Center: Materials Science and Engineering (Course 3)

MIT Faculty Supervisor Name: Jeffrey C. Grossman

Project Title: Development of Web-based framework for data management for the Consortium for Production of Affordable of Carbon Fibers

Project Description: We are seeking a highly motivated student for a Fall/IAP UROP to help develop a dynamic, user-friendly web frontend and backend to an internal MongoDB database to be used to manage experimental data from chemical precursor processing, synthesis, fabrication and performance of carbon fibers, through the Department of Energy sponsored Consortium for Production of Affordable Carbon Fibers (DoE-CPACF). This interface/database will support data collection, storage, and access 5+ institution and help the development the next generation of affordable carbon fibers, through advanced analytics.

The web-framework as envisioned may use Node.js based technologies for the back-end (Loopback or similar) with direct connection to the MongoDB database, and Angular (or similar) for the front end. The web interface will be designed to: (a) provide a virtual notebook to track device fabrication and performance, (b) provide a fully searchable platform for retrieving specific and aggregated device data.

The CPACF program is supported by the Department of Energy, focusing on development and scale-up of inexpensive and abundant chemical precursors as well as manufacturing methods for the large scale deployment of inexpensive carbon fibers for automotive, with resulting improvements in vehicle efficiency through significant weight reduction. The vertically integrated consortium involves academic, national laboratories and industrial members each involved in specific steps of the production of carbon fibers, from chemical precursors to composites. The Grossman Group in the Department of Materials Science and Engineering (DMSE, Course 3) directs and coordinates the data management, analytics and modeling for the program. Each member will use the MIT developed web-based data management framework for data collection.

Prerequisites: You will work with DMSE researchers to build, test, and fully document the front-end, backend and integration with mongoDB, based on data-structures under development through the program. Interested candidates should have extensive and documented experience in web-design and development using Node.js and web technologies (Loopback, Angular, etc) as well as MongoDB. Proficient hands-on experience with Python is desired. No specific Chemistry, Physics, Materials knowledge is required.

Contact: Nicola Ferralis (ferralis@mit.edu)


8/17/18

Term: Fall

UROP Department, Lab or Center: Urban Studies and Planning (Course 11)

MIT Faculty Supervisor Name: Jinhua Zhao

Project Title: The Value Proposition of Autonomous Mobility in the Developing World

Project Description: Autonomous vehicle technology promises to revolutionize how we move. Reduced congestion, cleaner air and, most notably, better road safety are all envisioned to be part of an autonomous mobility ecosystem. These benefits, particularly in regards to safety, have significance for emerging markets where traffic fatalities are disproportionately high compared to highly developed economies. Leveraging these benefits however, demands affordability relative to existing travel mode choices. As part of this effort, we are looking to improve understanding of the economics of travel choice in emerging markets and how the value proposition posed by autonomous vehicle technology compares to these choices. To that end, we are looking for a motivated, enthusiastic UROP with particular interest in economics and interdisciplinary sciences, to support our efforts.

The UROP will start with data already collected for the Beijing, China taxi industry and determine the capital and operating cost structure on a per-mile basis based on an existing example for San Francisco, CA. Additional UROP duties may include searching for and identifying appropriate data sets from public sources, constructing financial models, facilitating data analysis efforts and, where appropriate, conducting statistical analysis. Opportunities exist for co-authoring papers.

Prerequisites: Coding (in Matlab, python) and GUI development is considered a plus as is familiarity with the global transportation ecosystem. Of particular importance is intellectual curiosity and willingness to gain familiarity with interdisciplinary literature.

Relevant URL: https://mobility.mit.edu/

Contact: Joanna Moody (jcmoody@mit.edu)


8/17/18

Term: Fall

UROP Department, Lab or Center: Center for Transportation & Logistics (CTL)

MIT Faculty Supervisor Name: Dr. Jarrod Goentzel

Project Title: US Residential Construction Market

Project Description: Following major disasters, large numbers of homes are damaged, destroyed, or inaccessible.  Government assistance supports both temporary and transitional housing with a wide variety of tools – shelter, financial assistance, home repairs, and a hotel room.  The speed of disaster survivors’ return home can impact school reopening, local business recovery, and even tax revenue.

This research furthers existing work to characterize and quantify drivers in the US Residential Construction Market. The end-goal of the UROP is to draft an academic paper estimating the residential construction capacity in the United States. That end-goal will be accomplished by addressing the following sub-goals:

  • Developing a proxy to measure construction capacity for both new home construction as well as disaster-caused home repair
  • Determining the ability of home builders to relocate towards disaster repair work temporarily, via working alongside economists from the National Association of Home Builders
  • Determining the impact of professional licenses on the home repair and home construction labor pool.
  • Characterizing the importance of and level of access to financial capital for disaster reconstruction home builders

Additionally, this undergraduate researcher will be responsible for coordinating the speaker series for the Humanitarian Disaster Response Working Group.  That entails:

  • Every 4–6 weeks hold event with speaker: send out an event digest with contact information or a sign-up sheet
  • For larger events send out save the dates and a flyer
  • For those big events, print out a bunch and put them anywhere you see flyers
  • Need to concentrate on marketing events to get more students

Prerequisites:

This UROP should have a strong desire to:

  • Learn more about the US residential construction market
  • Build their expertise on the topic of disaster repair work
  • Communicate with experts in the construction market via phone and email
  • Work towards the ultimate benefit of future disaster survivors

Relevant URL: http://humanitarian.mit.edu/

Contact: Michael Windle (mwindle@mit.edu)


8/17/18

Term: Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Canan Dagdeviren

Project Title: Piezoelectric Sensing and Actuating of the Human Face

Project Description: Our body is an ocean of patterns that we have not yet properly decoded. Our lab, Conformable Decoders, works on translating these biological signals around us - especially from the human body - into energy and data that we can easily understand. We microfabricate the devices for energy harvesting and sensing in our very own cleanroom (YellowBox) at the Media Lab. In this project, the student will collaborate closely with the student advisor to fabricate tools needed to test the devices and conduct tests in the cleanroom. Specifically, this project is focused on creating invisible sensors for the face which will then be used to control a computer interface.

We are looking for one UROP who is experienced in fabrication of mechanical tools, especially X-Y stages. Tasks may include building a highly accurate X-Y linear stage for dynamic mechanical analysis and constructing a setup to read out force applied by the stage on a microfabricated device. You may also be asked to create more force-feedback sensor systems to incorporate with other microfabrication tools and design an interface which converts our custom piezoelectric sensor output to computer commands to move cursors, type, and more.

Prerequisites: We would like students who are careful, methodical, organized, and motivated. Though not required, prior experience in a research laboratory is preferred.  You must be well-versed in using machine shop tools such as lathe, mill, bandsaw, etc. If you have experience with designing circuits and laying out PCB’s, that’s a plus.

Contact: Farita Tasnim (farita@media.mit.edu)


8/17/18

Term: Fall

UROP Department, Lab or Center: Electrical Engineering and Computer Science (Course 6)

MIT Faculty Supervisor Name: Troy Littleton

Project Title: Developing analytical tools to study synaptic communication in a simple genetic model system

Project Description: The Littleton lab seeks to investigate the mechanisms of synaptic transmission and plasticity.  We are looking for course 6 or other engineering students to assist our efforts to develop analytical tools to analyze neural and synaptic data using MATLAB tools. We are interested to address the following: (Project 1) Develop image processing data analysis tools to automate the analysis of our synaptic and neural calcium imaging data [confocal and super-resolution nanoscopy data], (Project 2) Develop analytical tools (and machine learning tools) to quantify fly behavior and gene expression data.

Prerequisites: Great curiosity and enthusiasm to pursue multidisciplinary research. Although Candidates of all experience levels will be considered, preference will be given to candidates with a background in at least one of the following:

  • Experience with MATLAB preferred. Python or R background will also be considered.
  • Image/video analysis in MATLAB.
  • Signal processing in MATLAB.

Relevant URL: https://littletonlab.mit.edu/research

Contact: Suresh Kumar Jetti (sureshj@mit.edu)


8/15/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Josh McDermott

Project Title: Cross-cultural studies of music perception

Project Description: We plan to conduct a set of experiments comparing pitch and music perception in Americans and an indigenous Amazonian group (the Tsimane’). Previous studies in our lab have provided evidence, for example, that the Tsimane’ do not demonstrate an aesthetic preference for consonance over dissonance. This UROP opportunity will involve designing and running studies relating to music perception in the lab in Boston, and preparing for a data collection trip to Bolivia during summer 2019. The UROP will possibly be asked to join this trip.

This is an interdisciplinary project combining psychophysics, cross-cultural studies, and music cognition.

Prerequisites:

  • (1) Fluent Spanish
  • (2) Comfort in MATLAB
  • (3) An interest in working with human participants
  • (4) Outdoor/travel experience and comfort
  • (5) Must be available for Fall, Spring, and Summer 2018. Summer research may involve a 2-3 week trip to Bolivia. Schedule during semesters can be flexible.

Relevant URL: https://www.nature.com/articles/nature18635

Contact: Malinda J. McPherson (mjmcp@mit.edu)


8/15/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Laura Schulz

Project Title: Hypothesis generation and evaluation in young children

Project Description: How do children generate and evaluate hypotheses to novel problems? What features of problems and hypotheses impact these reasoning processes? This project involves two experiments: one on explanation and one on tool innovation. In the explanation experiment, we will tell various short stories to participants, ask them different questions, and test how they evaluate different explanations. In the tool innovation experiment, we will present a physical problem-solving task to participants, and see how they approach the problem. These 15-minute experiments will involve working closely with 4-6 year-old children. 

The UROP will be expected to perform the following tasks:

  • 1. Recruit and test participants at the Boston Children's Museum
  • 2. Process and upload video and behavioral data into database.
  • 3. Learn to perform data analysis using R
  • 4. Commit to at least 10 hrs/week
  • 5. (Optional) Attend weekly lab meetings 

Prerequisites:

  • 1. Prior experience working with children ages 4-6 is a plus. 
  • 2. Great interpersonal skills and patience, and ability to engage young children.

Contact: Regina Ebo (reginae@mit.edu)


8/15/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Laura Schulz

Project Title: Statistical Reasoning in Early Childhood

Project Description: Work on research questions relating to intuitive statistical reasoning in young children - for example, what do they understand about populations, sampling, and making rich inferences from data before they are explicitly taught these concepts? There are currently projects at different stages of development, from more established paradigms to new projects in pilot stages that we would love to have students be involved in depending on their interests and backgrounds. Most would involve data collection at the Boston Children's Museum a few shifts a week, working with children between the ages of 4-8 years. Beyond data collection, students are also welcome and encouraged to participate in experimental design and data analysis, as well as optional journal club with the graduate students and other UROPs in the lab. 

Prerequisites: 9.00 and 9.85 are preferred but not required.

Contact: Regina Ebo (reginae@mit.edu)


8/15/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Laura Schulz

Project Title: The systematic use of moral explanations

Project Description: In this project, we are exploring whether subjects systematically use a range of moral reasons to explain why an action was wrong.  We aim to figure out how subjects know which explanations apply to which moral violations.  Of particular interest to us is a moral explanation that derives from Kant's categorical imperative, or the "what if everyone did that" test.  Assisting with this project will involve collecting data from preschool aged subjects and/or older children, developing stimuli for children, and building online surveys to collect data from adults.  

Minimum commitment is 10-12/hours which includes at least 2 shifts at the Boston Children's Museum where research is conducted.

Contact: Regina Ebo (reginae@mit.edu)


8/15/18

Term: Fall/IAP

UROP Department, Lab or Center: Chemistry (Course 5) & Chemical Engineering (Course 10) 

MIT Faculty Supervisor Name: Daniel Anderson

Project Title: Design and study of glucose responsive materials

Project Description: Type 1 diabetes (T1D), also known as juvenile diabetes, is a growing health crisis all over the world with the total annual global costs amounting to US$500 billion including the treatment related to its complications. Self-administration of insulin injections, which is critical in maintaining a healthy normal blood glucose level, is an important component in managing diabetes. As the traditional insulin therapy is expensive, painful and inconvenient. This project will explore the next generation glucose-responsive chemosensors with physiologically relevant glucose-responsiveness.

Prerequisites:  We seek students with a strong background in chemistry or biochemistry

Relevant URL: http://anderson-lab.mit.edu/

Contact: Chandra Bhattacharya (cbhattac@mit.edu)


8/15/18

Term: Fall

UROP Department, Lab or Center: Computer Science and Artificial Intelligence Laboratory (CSAIL)

MIT Faculty Supervisor Name: Brian Williams

Project Title: Risk Bounded Trajectory Optimization for Robotic Systems

Project Description: The goal of this project is to generate feasible trajectories for robotic systems in the presence of probabilistic uncertainties and perturbations. The obtained trajectory should respect the defined constraints and also the risk bounds. Risk is defined as the probability of failure e.g., collision with obstacles. This problem is reformulated as an optimization problem with a proper cost function and deterministic constraints.

The UROP is required to 1) develop the MATLAB code given the mathematical formulation and the optimization algorithm, 2) generate the simulation examples for different robotic systems.

Prerequisites: MATLAB programming skills, Nonlinear optimization using SNOPT, Convex Optimization.

Relevant URL: http://jasour.mit.edu/RiskBoundedMotionPlanning

Contact: Ashkan Jasour (jasour@mit.edu)


8/15/18

Term: Fall

UROP Department, Lab or Center: Chemical Engineering (Course 10)

MIT Faculty Supervisor Name: Klavs F. Jensen

Project Title: Interpreting chemical reactivity predicted by machine learning models

Project Description: Machine learning is playing an increasingly important role in organic chemistry, especially in predicting chemical reactivity. Most models give black-box predictions that cannot be easily interpreted. However, it is important to be able to interpret the predictions which would help users understand model behavior, detect data issues and thus driving model improvement. For example, by understanding which training reactions have the strongest impact on the prediction made for a given test reaction, chemists can make better decisions.

The project aims at using statistical techniques to trace the model’s prediction through the learning algorithm and back to its training data, identifying the most responsible reactions for the given prediction. We are looking for a UROP to help with the model development. Familiarity with machine learning is desirable but not necessary, and knowledge (or passion) about organic chemistry would help you get more out of the project. Successful UROPs will have the opportunity to participate in other related projects.

Prerequisites: The project involves Python programming, so at least a moderate level of Python familiarity is required. Experience with logistic regression/neural network models is a plus.

Contact: Hanyu Gao (hanyugao@mit.edu)


8/15/18

Term: Fall/IAP

UROP Department, Lab or Center: Computer Science and Artificial Intelligence Laboratory (CSAIL)

MIT Faculty Supervisor Name: Daniela Rus

Project Title: Systems Integration for Autonomous Driving

Project Description: The Distributed Robotics Lab at MIT CSAIL is contributing to the development of self-driving cars within the Toyota-CSAIL joint research center. Our work addresses the full scope of challenges in the development of this new and exciting technology, involving theoretical and applied work on decision making, perception, and control.

In order to evaluate and validate our algorithms for different aspects of autonomous driving, we are operating several robotic platforms and simulation environments. Our platforms involve two Toyota Prius, two autonomous wheelchairs, and a set of miniature racing cars. The work of the UROP will involve supporting us in the development and maintenance of the software infrastructure for real-world robotic experiments.

Prerequisites:

  • Python and C++ programming experience (having written at least 10k lines of code in each language).
  • Knowledge of ROS and hands-on robotics experience.
  • Experience in using Linux (including bash, Makefiles, cmake, gcc, gdb).
  • Knowledge of modern software development methodology as presented in the software construction course or through internships (working with git, style guides, unit tests, code reviews)
  • Knowledge of some of the following technologies/frameworks is a big plus: OpenCV, PCL, Tensorflow, PyTorch, Gazebo, Jenkins, Docker.
  • Ability to work highly independently.

Students outside of EECS are also encouraged to apply. Please also consider applying if you have exceptional algorithmic skills (demonstrated through successful participation in competitions such as IOI or ICPC) and/or an extensive programming experience (having written over 50k lines of code spanning different programming languages and numerous different frameworks).

If you are interested, please apply with your CV and grade transcript. Work hours can be organized flexibly and are expected to be on average above 10h / week or full-time for IAP UROPs.

Contact: Igor Gilitschenski (igilitschenski@mit.edu)


8/15/18

Term: Fall/IAP

UROP Department, Lab or Center: Computer Science and Artificial Intelligence Laboratory (CSAIL)

MIT Faculty Supervisor Name: Daniela Rus

Project Title: Robust Perception for Autonomous Driving

Project Description: The Distributed Robotics Lab at MIT CSAIL is contributing to the development of self-driving cars within the Toyota-CSAIL joint research center. Our work addresses the full scope of challenges in the development of this new and exciting technology, involving theoretical and applied work on decision making, perception, and control.

Within this project, we are looking for a UROP interested in computer vision and, more broadly, perception for self-driving vehicles. Developing a robust perception system is key to maintaining situational awareness in highly dynamic environments which may undergo strong appearance and structural changes.  The work will involve the integration of existing Perception pipelines (e.g. for Object Detection or Simultaneous Localization and Mapping) and development of new tools for data processing and visualization.

Prerequisites:

  • Python programming experience (having written at least 10k lines of Python code).
  • Knowledge of Computer Vision covering the material of the courses 6.801/6.866 and ideally 6.819/6.869.
  • Experience with OpenCV and desirably PCL.
  • Experience in robotics,  having worked with real-world datasets for autonomous driving (e.g. KITTI or Oxford Robocar Dataset), or knowledge of some of the following technologies/frameworks is a big plus: C++, ROS, Tensorflow.
  • Students outside of EECS are also encouraged to apply.

If you are interested, please apply with your CV and grade transcript. Work hours can be organized flexibly and are expected to be on average above 10h / week or full-time for IAP UROPs.

Contact Name: Igor Gilitschenski (igilitschenski@mit.edu)


8/15/18

Term: Fall/IAP

UROP Department, Lab or Center: Computer Science and Artificial Intelligence Laboratory (CSAIL)

MIT Faculty Supervisor Name: Daniela Rus

Project Title: Deep Learning for Autonomous Driving

Project Description: The Distributed Robotics Lab at MIT CSAIL is contributing to the development of self-driving cars within the Toyota-CSAIL joint research center. Our work addresses the full scope of challenges in the development of this new and exciting technology, involving theoretical and applied work on decision making, perception, and control.

Deep learning has been successfully applied to different aspects of the autonomous driving task such as lane and vehicle detection as well as full end-to-end control. We are interested in developing novel algorithms for deep learning-based planning and control, quantifying and representing network uncertainty, neural network compression, and prediction of the state of the environment. The work of the UROP will involve implementation and development of neural network architectures and their evaluation with regard to one or several of these challenges on a full-scale autonomous vehicle.

Prerequisites:

  • Python programming experience (having written at least 10k lines of Python code).
  • Experience with at least one state-of-the-art Deep Learning framework (e.g., Tensorflow or PyTorch)
  • Experience with deep learning architectures for Sequence and Image modeling (LSTMs, CNNs).
  • Experience in robotics,  having worked with real-world datasets for autonomous driving (e.g. KITTI or Oxford Robocar Dataset), or knowledge of some of the following technologies/frameworks is a big plus: C++, ROS, OpenCV, PCL, Docker.
  • Students outside of EECS are also encouraged to apply.

If you are interested, please apply with your CV and grade transcript. Work hours can be organized flexibly and are expected to be on average above 10h / week or full-time for IAP UROPs.

Contact: Igor Gilitschenski (igilitschenski@mit.edu)


8/13/18

Term: Fall/IAP

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Danielle Wood

Project Title: Design of a Satellite Testbed

Project Description: The Space Enabled Research Group advances justice in Earth’s complex systems using designs enabled by space. Space technology contributes to the United Nations’ Sustainable Development Goals via communication, earth observation, positioning, microgravity research, spinoffs and inspiration. Space Enabled uses six research methods: design, art, social science, complex systems, satellite engineering and data science.

This project develops a satellite testbed that will help Space Enabled prepare to design future orbital spacecraft missions. The student will investigate satellite components to comprehensively understand electrical, mechanical, and communication constraints between each and integrate them into a physical testbed.

Prerequisites: We seek students with a strong background in embedded electronic systems, especially electrical, aerospace, and mechanical engineers. In addition, we seek students interested in the topic of sustainable development.

Relevant URL: spaceenabled.media.mit.edu

Contact: Javier Stober (stober@mit.edu)


8/13/18

Term: Fall

UROP Department, Lab or Center: Plasma Science and Fusion Center (PSFC)

MIT Faculty Supervisor Name: Richard Petrsso

Project Title: Inertial Confinement Fusion neutron spectrometer response function simulations with Geant4

Project Description: The High-Energy-Density Physics (HEDP) Division http://www-internal.psfc.mit.edu/research/hedp/ of the PSFC designs and implements experiments, and performs theoretical calculations, to study and explore the non-linear dynamics and properties of plasmas under extreme conditions of density (~1000 g/cc), pressure (~ 1000 gigabar), and field strength (~megagauss).  As part of this effort, the group has installed the MRS neutron spectrometer to measure the yield, ion temperature and confinement properties of Inertial Confinement Fusion (ICF) ignition experiments on the National Ignition Facility (NIF). This spectrometer measures neutron spectra from the primary cryogenically layered DT implosions on the NIF, such as described in Refs. [1,2,3]. MRS measurements from the NIF are interpreted using a detailed instrument response function simulated using the Geant4 toolkit (geant4.cern.ch). We are currently looking to improve our understanding of instrument response to allow more detailed analysis of finer features of the measured neutron spectra, as a step to understanding asymmetries and flows in the NIF implosions. These factors are crucial to understand and mitigate in order to achieve ignition on the NIF.

To accomplish this, we are looking for a student to:

  • (i) adapt the existing response function simulation code to the newest version of Geant4;
  • (ii) move the code from a Windows to a Linux computing environment;
  • (iii) add more physics capability to the code to further improve our understanding of MRS response.

Prerequisites: The right candidate for this project is a self-motivated student with prior experience in C++ and Linux. Geant4 experience would be an advantage, but for a student that does not yet know Geant4, this is an excellent opportunity to learn! Hours for this project will be negotiable, during Fall 2018 and with the possibility of continuing into future semesters.

Relevant URLs: http://www.psfc.mit.edu/  | http://www.psfc.mit.edu/research/topics/high-energy-density-physics

Contact: Maria Gatu Johnson (gatu@psfc.mit.edu)


8/9/18

Term: Fall/IAP

UROP Department, Lab or Center: Civil and Environmental Engineering (Course 1)

MIT Faculty Supervisor Name: Prof. L. Bourouiba

Project Title:  Biophysics and infectious diseases

Project Description: The Fluid Dynamics of Disease Transmission Laboratory focuses on elucidating the dynamics of pathogen transmission from the lens of physical processes at various scales. A series of ongoing projects involve the development and analysis of experimental results derived from high-speed imaging, microfluidics, and microscopy.

We seek a driven UROP student with a strong background in physics or Math-Physics to be involved in some of these projects. The range of tasks, depending on the student background, will range from involvement in experimental data collection, microscopy, to data analysis.

Prerequisites: We are looking for a UROP student with a positive outlook and personality, and the ability to give and take constructive criticism, and with particular interest in working on problems pertaining to the application of physics and engineering to health challenges. Optics and coding (e.g., Matlab, python, development of GUIs) are considered assets.

If interested, please send an updated CV, including the list of courses taken and previous projects/UROP experiences to Prof. L. Bourouiba lbouro@mit.edu.

Relevant URL: http://lbourouiba.mit.edu/

Contact: Prof. L. Bourouiba (lbouro@mit.edu)


8/9/18

Term: Fall/IAP

UROP Department, Lab or Center: Civil and Environmental Engineering (Course 1)

MIT Faculty Supervisor Name: Prof. L. Bourouiba

Project Title: Algorithms for mitigation and control of infectious diseases

Project Description: Infectious diseases continue to persist and infect millions per year (e.g., influenza, SARS, and C-difficile to cite a few). In addition, the emergence of resistant strains (super-bugs) will be one of the most pressing challenges of the century. To develop a multifaceted approach to mitigation and control of infectious diseases and curb the risk of epidemics and pandemics, it is important to understand the process of transmission. Such understanding will allow for new engineering solutions to transmission mitigation.

The Fluid Dynamics of Disease Transmission Laboratory focuses on developing the tools to study, and deriving fundamental insights on, the dynamics of pathogen transmission. A series of projects aiming to do so involve biophysics, signal processing, and pattern recognition to be developed for novel experimental and medical datasets. For these projects, we seek a driven UROP with a strong background in signal processing and associated algorithm development to assist with signal pattern recognition and extraction.

We seek a dedicated and motivated UROP student with positive outlook and personality, and the ability to give and take constructive criticism. It is important that the UROP student be interested in remaining involved in the laboratory for more than one term, to enable sufficient time for receiving training, and have the opportunity to apply such training to make significant progress on the project selected, hence fully benefit from this unique research opportunity.

Prerequisites: Experience with coding in a range of languages, development of GUIs, and particular interest in working on problems pertaining to human health applications combined with strong quantitative and analytic skills in physics or Math-Physics will be considered assets.

Contact: If interested, please send an updated CV, including the list of courses taken and previous projects/UROP experiences to Prof. L. Bourouiba lbouro@mit.edu

Relevant URL: http://lbourouiba.mit.edu/


8/9/18

Term: Fall

UROP Department, Lab or Center: Health Sciences and Technology (HST)

MIT Faculty Supervisor Name: Jonathan Polimeni, PhD

Project Title: The effect of brain orientation in functional Magnetic Resonance Imaging 

Project Description: Magnetic resonance imaging (MRI) is used to study neuronal activity in the human brain non-invasively. These signals are derived from blood oxygenation, flow and volume changes in the brain’s vasculature that cater for the increased metabolic demand during neuronal activity. Functional MRI (fMRI) techniques have been refined and pushed to higher spatial and temporal resolution over the last decade. The hope is to enhance neuronal specificity with higher resolution, however there is evidence that higher resolution makes these signals more susceptible to vascular properties, in particular the orientation of vessels to the magnetic field. This project aims to assess these biases in a large data set (the Human Connectome Project).

We are looking for a student with a background in either CS, Physics, EE or similar that is interested in learning more about fMRI and the human brain. No prior knowledge in neuroscience is required. Most of the work will comprise bash scripting and data analysis in Matlab. The student will gain experience in specific software for brain imaging data, handling large data sets, signal processing and brain physiology (cool!).

Prerequisites: Comfortable with LINUX/UNIX and Matlab, some experience in bash scripting (or willing to get some), some knowledge in computer graphics would be a plus.

Contact: Olivia Viessmann oviessmann@mgh.harvard.edu


8/9/18

Term: Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Hugh Herr

Project Title: Camera-based 3D scanner for biomechanical applications

Project Description: In order to design subject-specific biomechanical interfaces, such as the prosthetic socket for amputees, accurate knowledge of the shape, deformation, and mechanical properties of the body part is essential. At the Biomechatronics group of the MIT Media Lab, we develop a 360-deg 3D scanner and indentation device for measuring the shape of the residual limb, as well as the full-field deformations and strains on the skin, and the mechanical properties of the underlying soft tissues. The system employs synchronized multiple Raspberry Pi camera boards and ATI force/torque sensors. An open source MATLAB toolbox (https://github.com/MultiDIC/MultiDIC ) was developed to analyze images from multiple cameras and reconstruct the 3D shape and deformations, using 3D Digital Image Correlation.

The UROP student is expected to conduct 3D Digital Image Correlation analysis on images acquired by the 3D scanner in MATLAB, and assist with further development of the software. UROP students will have the opportunity to participate in clinical experiments where the developed systems will be tested on patients with lower limb amputation.

Prerequisites:

  1. Prior experience programming in MATLAB.
  2. Commit to at least 10 hrs/week.
  3. Prior research experience is a plus.

Please send your CV as well as a description of any experience/projects relevant to this position.

Relevant URL: https://github.com/MultiDIC/MultiDIC

Contact: Dana Solav (danask@mit.edu)


8/9/18

Term: Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Hugh Herr

Project Title: Pressure sensing system for prosthetic sockets

Project Description: At the Biomechatronics group of the MIT Media Lab, we develop a methodology for computationally designing and 3D printing prosthetic sockets for lower limb amputees. The socket comprises the mechanical interface between the soft tissue of the residual limb and the external prosthesis. In order to evaluate the fit of the socket, accurate measurement of the pressure applied on the skin by the prosthetic socket is required. A pressure sensing system is developed, which include thin pressure sensors and an Arduino-based data acquisition system. The UROP student is expected to perform the following:

  1. Develop and build electronic circuits for acquiring pressure measurements from multiple sensors simultaneously.
  2. Program Arduino/Raspberry Pi type boards for data acquisition.
  3. Perform calibration and validation tests of the system.

UROP students will have the opportunity to participate in clinical experiments where the developed systems will be tested on patients with amputation.

Prerequisites:

  1. Prior experience with electronics and Python programming.
  2. Commit to at least 10 hrs/week.
  3. Prior research experience is a plus.

Please send your CV as well as a description of any experience/projects relevant to this position.

Relevant URL: https://www.media.mit.edu/projects/variable-impedance-prosthetic-vipr-socket-design/

Contact: Dana Solav (danask@mit.edu)


8/9/18

Term: Fall/IAP

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Ahmed Ghoniem

Project Title: Arduino and control system for a decentralized biomass/renewable energy system

Project Description: In many parts of the developing world, agricultural and other biomass waste is simply burned in the open air, creating much toxic pollution. Thermochemical treatment is a process whereby this waste can be converted into solid fuel. This has the potential to provide renewable energy, create new income and jobs, reduce waste, and in some cases cut down pollution and greenhouse emissions.

To make the system run more effectively, we have built a preliminary Arduino system to control the reaction conditions with minimal user intervention. This UROP will be a continuation of the project in further developing the system to incorporate temperature feedback and smart adjustment. Successful projects will have potential follow-on travel opportunities (India, Kenya, etc.) to test viable prototypes.

Prerequisites: Prior experience with circuit design and Arduino platform is required. Multi-semester engagement strongly preferred. Please send CV to kkung@mit.edu in case of interest.

Relevant URL: http://tatacenter.mit.edu/portfolio/torrefaction-reactor/

Contact: Kevin Kung (kkung@mit.edu)


8/9/18

Term: Fall/IAP

UROP Department, Lab or Center: Materials Processing Center (MPC)

MIT Faculty Supervisor Name: Lionel C. Kimerling

Project Title: Educational Games for Integrated Photonics Virtual Lab

Project Description: Would you like to develop educational tools to help students learn about optics and photonics? Are you interested in gaining skills in optical modeling and simulation?

Photonic integrated circuits (PICs) are an emerging technology that combine electronic and photonic devices on the same platform. Our goal is to create a library of educational simulations for workforce training in this new field.

In this project you will learn to use commercial software to explore photonic device behavior and incorporate your results in an online Virtual Lab. We have an expert production team, including a full-time software developer and UI/UX designer, as well as two content experts to help guide the project.

Sponsored research funding is available. Preference will be given to applicants who can commit ~10 hrs/wk during fall term and 40 hr/wk during IAP. For sophomores and juniors, this position could be open to a longer-term commitment.

Prerequisites: Must have a background in applied physics or materials science. Experience with commercial optical simulation tools (Lumerical / Synopsys) is a plus, but not necessary.

Relevant URL: https://aimphotonics.academy/about/what-integrated-photonics

Contact: Dr. Erik Verlage (everlage@mit.edu)


8/9/18

Fall 2018

Department/Lab/Center: Research Lab for Electronics (RLE)

Faculty Supervisor: Prof. David Perreault

Project Title: Investigating High-Frequency Magnetic Materials for Power Electronics

Project Description: Power conversion is crucial for many applications, ranging from medical equipment to electric vehicles to consumer electronics. One of the major challenges in power electronics is designing small, low-loss magnetic components (inductors and transformers). To do this well, designers need to know the loss properties of magnetic core materials so that they can select the appropriate material for their application. However, many systems are now pushing to higher frequencies of operation for miniaturization, and core loss information at these frequencies is difficult to measure, even for the manufacturer. To help solve this, our lab has been leading research into methods to characterize magnetic materials at high frequencies.

Currently, every available high-frequency measurement approach is very manual and time-consuming. This UROP will research automated approaches, combining insights from power electronics, analog and digital circuits, signal processing, and embedded systems.  This work will directly enable materials manufacturers to characterize and develop better HF materials, with high impact in the power electronics industry.  The results of this work will be published, and it will be used by lab members, as well as other research and industry groups. 

Through this project, the UROP will gain hands-on experience in electromagnetic and circuit analysis, PCB design, and electrical and mechanical prototyping.  These skills are highly desirable both in industry and academia.  

Prerequisites: 6.002 or equivalent experience

Expected Commitment: 10 hours/week

Contact: Prof. David Perreault (djperrea@mit.edu), Alex Hanson (ajhanson@mit.edu), Rachel Yang (rsyang@mit.edu)


8/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Canan Dagdeviren

Project Title: Interfacing with Intelligent Textiles

Project Description: The Conformable Decoders group are currently developing a collection of smart garments through digital knitting technologies for physiological sensing, activity monitoring, and physical interaction applications. Depending on the background, skills, and interests, the UROP student will be expected to perform one/several of the followings:

  • Construct multiplexing circuit for large-scale sensing
  • Develop wireless communication interface
  • Analyze sensor data and apply pattern recognition principles

A successful UROP will have the option to extend the project into the following term. To take a part in this exciting project, please send your resume and interest to irmandy@mit.edu.

Prerequisites: Are independent, dedicated, imaginative, and creative. Possess great organizational and communication skills. Have experience in one or more of the followings: sensor interface, wireless communication, PCB design, machine learning, or programming.

Contact: Irmandy Wicaksono (irmandy@mit.edu)


8/6/18

Term: Fall

UROP Department, Lab or Center: Sloan School of Management (Course 15)

MIT Faculty Supervisor Name: Yasheng Huang

Project Title: Government Regulations of Food Safety in China

Project Description: The goal of this project is to find Chinese data and archival and documentary sources that will help our understanding of the roles and functions of government regulations and management of risks associated with the intentional adulteration of food supply chains (i.e., poultry, beef, pork, milk, seafood, and produce) in China. The data and archival sources may come from government websites, government publications on regulations, court cases, media reports. The UROPs will work in a supervised team and will perform background research on the Chinese regulatory system and CFDA (related to food). Our aim is to map out potentially contaminated food suppliers using this data, creating a real-time social sensor of food safety in China.

Prerequisites: The focus here will be on identifying Chinese websites and other sources of data and information so ability to read and understand Chinese is necessary, general knowledge of and an interest in Chinese economy, politics and society and also the ability to write research reports and research summaries will be critical. Attention to details, the ability to finish tasks on time and initiative taking are extremely important.

Contact: Channa Yem (channay@mit.edu)


8/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Political Science (Course 17)

MIT Faculty Supervisor Name: Prof. Stephen Van Evera and Dr. John Tirman

Project Title: MIT and Israeli-Palestinian Bridge Building Initiatives

Project Description: MIT is currently is doing significant work in Israel, Jordan and with

Israeli-Palestinian projects. Last semester MIT students interviewed Israeli-Palestinian joint ventures/projects. We want to take this research to the next level by exploring the unique role that MIT can play to significantly impact, support and scale bridge-building between Israelis and Palestinians through science, technology and business, while enhancing MIT students’ global experiences and faculty’s capacity to partner with others to solve regional challenges.

Assignments will include:

  • Mapping of Israeli-Palestinian joint ventures/projects
  • In-depth interviews with a select group of Israeli-Palestinian ventures/projects that will enable a clear vision of MIT’s potential role in supporting their efforts.
  • Meeting with MIT centers/initiatives/groups to understand their potential role.
  • Assessing viability and ways of MIT engaging with these initiatives in order to significantly impact bridge building between Israelis and Palestinians, MIT engagement needs to include students travel to the region or faculty research/projects/classes
  • Engaging with participants that will be taking part in an Israeli-Palestinian conference at MIT, on Sunday November 11th, in order to solidify a vision and concrete steps for MIT engagement.
  • May include additional work focused on Nov. 11th event
  • May be widened to include Israel and Jordan

Prerequisites:

  • Current MIT student
  • Knowledge of the region
  • Not required, but travel to the region during IAP 2019 or summer 2019 may be possible
  • Academic or other experience in the Middle East is helpful
  • Strong analytical skills

Contact: David Dolev (ddolev@mit.edu)


8/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Biology (Course 7)

MIT Faculty Supervisor Name: David Bartel

Project Title: MicroRNA biogenesis

Project Description: MicroRNAs are ~ 22 nt endogenous RNAs that target mRNA post-transcriptionally to decrease protein output.  A mammalian genome encodes hundreds of microRNAs, which collectively regulate the majority of the transcriptome. Accumulating evidence suggests that microRNAs play key roles in diverse biological processes.  This project aims at understanding the molecular mechanisms by which microRNAs are made.  The UROP will work closely with Wenwen Fang, a postdoc researcher in the lab with extensive training in molecular biology and biochemistry. The UROP will participate in and learn about culturing human or mouse cells, and generating cell lines by CRISPR technology; perform biochemical and imaging experiments; prepare next generation sequencing libraries and carry out data analysis.

Prerequisites: Self-motivated student, general biology course (understanding of general biology), previous research experience preferable.

Contact: Wenwen Fang (wfang@wi.mit.edu)


8/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Ahmed Ghoniem

Project Title: Testing a decentralized biomass upgrading system

Project Description: In many parts of the developing world (including the U.S.), crop and forest residues are simply burned in the open air, creating air pollution. Thermochemical treatment is a process whereby such residues can be upgraded into solid fuel or other chemicals. This has the potential to provide renewable energy, create new income and jobs, reduce waste, and in some cases cut down pollutions and greenhouse emissions.  We work on small-scale, low-cost, portable systems that can potentially be latched onto the back of tractors, shipping containers, etc. to locally convert/upgrade the biomass residues at source.

You will assist in operating and testing a laboratory-scale version of the system. You will learn the basics of experimental design and data acquisition. This is a hands-on project -- expect to get your hands (really) dirty.

Unlike the previous related UROP position in decentralized biomass offered by our lab, this UROP position requires no previous technical experience. Compared to the other position, this specific position will be somewhat more tedious/repetitive as it consists of assisting the operation of our biomass system under various conditions. If you have no prior experience, however, this may be a good entry-level UROP position and a stepping stone to other more interesting projects within our groups in subsequent semesters once you gain more advanced experience and skills.

Please send CV to kkung@mit.edu in case of interest.

Prerequisites: As the system requires many hours of operation to finish a test, a preferred candidate will have one large chunk of many hours open on his/her weekly schedule, rather than multiple small chunks of time.

Relevant URL: http://tatacenter.mit.edu/portfolio/torrefaction-reactor/

Contact: Kevin Kung (kkung@mit.edu)


8/6/18

Term: Fall/IAP

UROP Department, Lab or Center: Mechanical Engineering (Course 2)

MIT Faculty Supervisor Name: Ahmed Ghoniem

Project Title: Developing and testing hardware components for a decentralized biomass upgrading system

Project Description: In many parts of the developing world (including the U.S.), crop and forest residues are simply burned in the open air, creating air pollution. Thermochemical treatment is a process whereby such residues can be upgraded into solid fuel or other chemicals. This has the potential to provide renewable energy, create new income and jobs, reduce waste, and in some cases cut down pollutions and greenhouse emissions.  We work on small-scale, low-cost, portable systems that can potentially be latched onto the back of

tractors, shipping containers, etc. to locally convert/upgrade the biomass residues at source.

You will help develop a critical hardware component and its software control within such a system. This is a hands-on project -- you will learn how to define functional requirements, source and purchase parts, test that they meet the functional requirements, and implement a control system to be able to adjust the component autonomously.

Please send CV to kkung@mit.edu in case of interest.

Prerequisites: An ideal candidate will have had experience with mechanical components and design, instrumentation (e.g. load cells), programming (e.g. Python), and basic circuit design (e.g. implementation of an Arduino-based control system). If you already have a design portfolio website, please send that along with your CV.

Relevant URL: http://tatacenter.mit.edu/portfolio/torrefaction-reactor/

Contact: Kevin Kung (kkung@mit.edu)


8/3/18

Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Canan Dagdeviren

Project Title: Assessing pH sensing materials and configurations for biomedical applications

Project Description: Recently, researchers developed miniaturized pH sensing systems for various biomedical applications, such as monitoring healing wounds, ischemic heart, and tumor tissues pH. These advancements rely on various sensing electrode materials and structures, including metal oxides, polymers, and various nanostructures. Our project aims at exploring suitable materials that are easy to fabricate and cost effective for pH sensing, given the strict reliability requirements for use in biomedical applications. Key evaluation parameters include sensitivity, stability, repeatability, reproducability, and the trade-offs associated.

The project tasks include:

  1. Participating in the design of experiments and tests planning.
  2. Configuring equipment and setup for pH experiments.
  3. Conducting pH measurements in class 10,000 cleanroom.
  4. Analyzing data and constructing professional plots.
  5. Surveying prior literary works and staying up to date on relevant topics.
  6. Contributing to manuscripts preparation through writing and editing.

 ** Representative literature on the topic:

    http://www.mdpi.com/1424-8220/9/11/8911/htm

    http://www.mdpi.com/1424-8220/9/9/7445/htm

Prerequisites: We are looking for self motivated, hard working, and observant candidates who are willing to learn quickly and are able to deal with uncertainty. A background in analytical chemistry, solid state electronics, and prior lab experience are preferred.

Contact: Mohamed Tarek Ghoneim: mohamed.t.ghoneim@gmail.com


8/3/18

Fall/IAP

UROP Department, Lab or Center: Electrical Engineering and Computer Science (Course 6)

MIT Faculty Supervisor Name: David J. Perreault

Project Title: Design Considerations for Hybrid Electronic and Magnetic Power Transformers

Project Description: Our group has developed a new class of transformer structure that combines electronic switches with the magnetic structure of a conventional transformer. Initial work on this structure has shown it to be highly beneficial in miniaturizing isolated power electronic converters (i.e. making them smaller and more efficient), making it attractive for emerging applications such as USB Type-C chargers, electric vehicles, and photovoltaic systems.

While the fundamental theory is understood, efforts to optimize this structure are still in their infancy. In this position, the UROP student will work closely with the graduate mentor to understand the critical but unexplored phenomena that are essential to optimizing this new class of transformer. In this endeavour, the student will have the opportunity to:

  • Develop 3-D Finite Element Model simulations to assess hypotheses that the student and mentors develop about possible limitations of the structure.
  • Design and evaluate hardware prototypes to verify the principles learned from simulation.
  • If the results of this investigation are positive, we will use the knowledge gained to formalize a set of design considerations for the structure and develop an optimized prototype.

The project is designed with a two-semester commitment in mind, with the intent to submit the work to an IEEE conference in 2019 (e.g. COMPEL 2019). There is also the option to continue with the lab on future projects.

Prerequisites: A strong background in circuits, ideally having completed or planning to take 6.334 (Power Electronics). A 10 hour/week commitment is expected, including weekly one-hour meetings together with the faculty supervisor.

Contact: Mike Ranjram: mranjram@mit.edu


8/3/18

Term: Fall

UROP Department, Lab or Center: Brain and Cognitive Sciences (Course 9)

MIT Faculty Supervisor Name: Prof. Ann Graybiel

Project Title: Testing the role of the striosome and matrix compartments in decision making

Project Description: Over the last decades big advances have been made in understanding the role of striatal pathways in behavior and cognition. However, still very little is known about the functional role of 2 major compartments, the striosomes and matrix. In this project we use optical methods to record from and manipulate these two compartments in behaving animals in order to test how the striosomes and matrix contribute to behavior.

Your work will consist of performing behavioral tests on mice and manipulating specific parts of the striatal circuitry using optogenetics. In addition, you will learn histological techniques and do data analysis.

Requirements: We are looking for a highly motivated student who is dedicated and eager to learn state of the art neuroscience methods. Work will take between 9 and 18 hours a week. We strongly prefer a student who wants to commit to this project for at least a year.

Contact: Please send you CV and a cover letter to Bernard   (bbloem@mit.edu)


8/3/18

Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Canan Dagdeviren

Project Title: Piezoelectric Energy Harvesting and Sensing from Biomechanical Motion at Knee

Project Description: Our body is an ocean of patterns that we have not yet properly decoded. Our lab, Conformable Decoders, works on translating these biological signals around us - especially from the human body - into energy and data that we can easily understand. We microfabricate the devices for energy harvesting and sensing in our very own cleanroom (YellowBox) at the Media Lab. In this project, the student will collaborate closely with the student advisor to fabricate tools needed to test the devices and conduct tests in the cleanroom.

Depending on your expertise and interest, tasks may include:

  1. Conducting finite element analysis to model piezoelectric thin film devices
  2. Building a motorized, silicone knee model for cycling tests of the devices
  3. Making host substrates for the microfabrication process
  4. Probing piezoelectric devices and interfacing to circuitry

We are looking for two UROPs.

Prerequisites: We would like students who are careful, methodical, organized, and motivated. Working in the cleanroom as an undergraduate is an amazing opportunity - you will appreciate it. Though not required, prior experience in a research laboratory is preferred.  Exposure to fabrication (laser cutter, CNC/manual mill, simple electronics, etc.) is a plus. If you are experienced in finite element analysis, that’s a major plus.

Contact: Farita Tasnim: farita@media.mit.edu


8/2/18

Term: Fall/IAP

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Canan Dagdeviren

Project Title: Wearable and Implantable Ultrasound Systems

Project Description: The Conformable Decoders group are currently fabricating flexible and stretchable electronic devices based on piezoelectric materials for medical imaging purposes. Depending on the background, skills, and interests, the UROP student will be expected to perform one/several of the followings:

  • Conduct literature review of the prior work of their research
  • Model and characterize theoretically or experimentally, piezoelectric transducer devices and polymer composites
  • Design templates, fabricate, and populate piezoelectric crystal arrays

A successful UROP will have the option to extend the project into the following term. Please send your resume and interest about this project to irmandy@mit.edu.

Prerequisites: Are independent, dedicated, imaginative, and creative. Possess great organizational and communication skills. Have experience in one or more of the followings: analog/digital electronics, PCB design, sensor fabrication and characterization, signal processing, modeling and simulation, medical imaging, or programming.

Contact: Irmandy Wicaksono (irmandy@mit.edu)


8/1/18

Term: Fall

UROP Department, Lab or Center: Biological Engineering (Course 20)

MIT Faculty Supervisor Name: Jim Collins

Project Title: Website Design for a Synthetic Biology Educational Non-Profit

Project Description: The Jim Collins’ lab at MIT’s Institute of Medical Engineering and Science (IMES) and Department of Biological Engineering is seeking a highly motivated student to do website graphic design for one of our research projects, BioBits. BioBits is an educational kit with hands-on, easy-to-use, low-cost molecular and synthetic biology activities for low-resource schools. We would like to further develop our current website (mybiobits.org) to include more information for interested teachers about our technology and the kits offered.

This UROP responsibilities will include:

  1. Develop and maintain a robust style guide for the BioBits website
  2. Create visual designs for web, mobile, email, and print collateral
  3. Work closely with the researchers to iterate on designs
  4. Create high-fidelity mock-ups and finished .sketch files for development
  5. Learn about the synthetic biology technology behind BioBits in order to develop content for the website

We expect the UROP to dedicate 10-20 hours a week to this project. We are looking for UROPs with an innate, sharp aesthetic and sense of style, a passion for design, a positive outlook and personality, and the ability to give and take constructive criticism

Benefits from this UROP opportunity include:

  • 1) contributing to an initiative that is seeking to provide quality biology education to students who normally cannot access it
  • 2) building your web design portfolio
  • 3) flexible working hours, as the design can be done out of lab
  • 4) opportunity to work in one of the top synthetic biology labs and learn more about our synthetic biology efforts for low-resource areas (hands-on wet lab experience possible, if desired by UROP)
  • 5) compensation of $12/hour.

To apply, please email Ally Huang (ally@mit.edu) your current resume and if possible, any samples of previous web design work you have done. Seeking applicants ASAP who can make a firm commitment on this project and start right away.

Prerequisites: Please provide details on any prerequisites or skills required for this UROP

Relevant URL: mybiobits.org

Contact: Ally Huang (ally@mit.edu)


8/1/18

Term: Fall

UROP Department, Lab or Center: Architecture (Course 4)

MIT Faculty Supervisor Name: Miho Mazereeuw

Project Title: Urban Risk Map - Machine learning for hyperlocal disaster alerts

Project Description: The Urban Risk Lab is an interdisciplinary research lab in School of

Architecture + Planning, developing technologies to embed risk reduction and preparedness into the design of cities. We are looking for students with prior experience, or a strong interest in machine learning to contribute in ongoing development work of the Urban Risk Map project. Urban Risk Map harnesses the power of citizen reporting and social media to map time-critical information without needing to install any new applications or training. Currently operating in three countries - Indonesia, India and the United States - this platform connects residents, who often have the best-localized information, with emergency managers to drastically cut down on response times.

The student will work closely with faculty and researchers to develops smart hyperlocal disaster alerts for Urban Risk Map - an open source platform for time-critical information sharing. The student will help support the project goals to: (1) Develop algorithms for detecting critical flood events using streaming crowdsourced data in conjunction with other geospatial datasets; (2) develop methods to use social media advertising for situational alerts (3) Assist with development of open source Riskmap platform for real-time disaster reporting.

Prerequisites:

  • JavaScript and python web-development experience
  • Familiarity with AWS preferable but not required
  • preferably have taken 6.036 and/or 6.171

Relevant URL: riskmap.org

Contact: Miho Mazereeuw (mmaz@mit.edu)


8/1/18

Term: Fall/IAP

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Danielle Wood

Project Title: Exploring the Dynamics of Learning and Decision-Making to Apply Space Technology in Support of Sustainable Development

Project Description: The Space Enabled Research Group advances justice in Earth’s complex systems using designs enabled by space. Space Enabled uses six research methods to apply space technology to sustainable development: design, art, social science, complex systems, satellite engineering and data science. In this project, Space Enabled emphasizes the use of design thinking and social science to understand the experiences of participants in projects that apply space technology in support of sustainable development. Specifically, the project uses methods from anthropology, sociology, history and economics to explore social aspects of technology projects. Several case study technology projects are examined in Malaysia, Vietnam, Thailand, Benin and Tunisia; in each case study an organization applies space technology to respond to a local need in a new way. All the case studies examine project that use space technology because this is an increasingly feasible opportunity for countries in every region of the world. The case studies ask questions such as: 1) What sociotechnical imaginaries does the community hold about the impact of space technology on their community? 2) What learning processes are used to learn new technology? In this project, students will analyze data for existing case studies and help prepare to collect data for future case studies. Students will also participate in literature review on the topics of cultural impacts of technological learning and the influence of technology on decision making.

Prerequisites: We seek students with a combined interest in social science and science or technology. We prefer students with knowledge in any of the following fields: sociology, anthropology, economics, political science, organizational theory, history, urban studies and planning, international studies. Students that have experience coding qualitative interview data and performing academic literature reviews are preferred. In addition, we seek students interested in the topic of sustainable

development.

Relevant URL: spaceenabled.media.mit.edu

Contact: Javier Stober (stober@mit.edu)


8/1/2018

Term: Fall/IAP

UROP Department, Lab or Center: Media Laboratory MIT Faculty Supervisor Name: Danielle Wood

Project Title: Designing Systems to Combat Invasive Plant Species in West Africa

Project Description: The Space Enabled Research Group advances justice in Earth’s complex systems using designs enabled by space. Space Enabled uses art, design, social science, complex systems, satellite engineering and data science to apply space technology to development. This project applies all six methods to the issue of invasive plants in West Africa. This project is pursued in collaboration with a company based in Cotonou, Benin called Green Keeper Africa that harvests the invasive water hyacinth and uses it to manufacture products that clean oil-based waste. Green Keeper Africa faces a challenge to monitor the location of the water hyacinth; they propose to create an Observing System to track the behavior of the plant. Space Enabled  and Green Keeper Africa are collaborating on a multi-faceted research project that will harness all six of the Space Enabled research methods. The project uses design thinking to identify the objectives for an information system.

The social science portion examines the historical, economic and cultural context. The complex system modeling activity builds a computer-based simulation of the community and environment. The engineering component aims to produce new data about the water hyacinth, such as building earth observation platforms. The data science work builds a prototype information system with actionable information about the water hyacinth. Students will join the activities outlined above, depending on their interests and background. The option to renew for spring may be available.

Prerequisites: We are looking for students with a technical background in GIS and remote sensing.  Also, students with backgrounds in biology; urban studies; social science (history, anthropology, sociology, economics); civil, environmental, mechanical and/or aerospace engineering; or computer science/data science are encouraged to apply. In addition to this technical background, we seek students with an interest in sustainable development. Prior research experience is preferred.

Relevant URL: spaceenabled.media.mit.eduContact: Javier Stober (stober@mit.edu)