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

11/9/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Yoel Fink

Project Title: Digital Fibers for Fabric Computing

Project Description: Logic is the ability in humans and computers enabling memory storage and decision processing. Incorporating logic functionality in fibers can thus empower highly intelligent fabrics. Here, we design and fabricate digital fibers with logic chips that can receive, process and send discrete signals, allowing information such as music, text and decision-making codes to be stored within the fabrics itself.  We are seeking UROPs to assist us in doing electrical characterization of our digital fibers, programming codes into these fibers and interfacing these digital fibers with other sensors for biomedical applications. The UROPs can expect to learn more about digital circuits, material studies on thermal drawing and electrical connections, and hardware programming with microcontrollers such as Arduino, PICAXE and Espruino.

Prerequisites: The project is open to students majoring in material engineering, electrical engineering, computer science, mechanical engineering, and other relevant fields. The UROP must have experience in coding (any languages such as Python, C, Javascript or others)

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

Contact: Gabriel Loke (gabloke@mit.edu)


11/9/18

Term: IAP

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

MIT Faculty Supervisor Name: Jon Gruber

Project Title: MIT Research to Public Policy Mapping

Project Description: The mission of the International Policy Lab (IPL) is to enhance the impact of MIT research on public policy. The IPL works with faculty from across the Institute to better connect their research to the decision makers who are able to act on it. As policy making becomes increasingly technical it will be vitally important that the knowledge created in Universities is properly applied to the policy making process.

In an effort to further develop such connections the IPL has begun an initiative to map all research conducted at MIT to corresponding policy domains. This project has three main goals. 1) To make MIT researchers more aware of the policy implications of their work, 2) to identify high impact opportunities for researchers to engage with policy makers, and 3) to facilitate the development of evidence-based policy both domestically and internationally.

This stage of this research project will focus on mapping out stakeholders in specific policy domains and developing a system of horizon scanning to identify policy opportunities.

Prerequisites: Ideal candidates will come from any School at MIT and will be comfortable drilling down to understand the technical details of multiple research programs. An interest in the application of research to the development of public policy is preferred but no policy experience is required. Training will be provided by MIT’s Washington DC office.

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

Contact: Dan Pomeroy (dpomeroy@mit.edu)


11/9/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: William Green

Project Title: Laser Detection of Transient Species in Fuel Combustion

Project Description: The burning of organic fuels remains the primary source of power for transportation and industrial sectors around the world. Untangling the complex chemistry that occurs during combustion is the key to improving engine designs and reducing undesirable emissions from both traditional fossil fuel and renewable biofuels. The Green group combines theory, experiments and computer science to develop tools for accurately predicting the important elementary reactions in combustion and other processes. Of particular importance are reactions involving molecules with unpaired electrons (radicals) and aromatic rings (benzene), which are abundant in combustion and lead to the formation of polycyclic aromatic hydrocarbons (PAHs) which are suspected cancer-causing agents. These reactions are difficult to explore experimentally due to the transient nature of both the reactants and intermediates.

We seek a UROP to assist in our Chemical Dynamics Laboratory measuring gas-phase reaction kinetics and product channel branching ratios with the unique combination of two highly sensitive experimental methods: laser absorption and time-of-flight mass spectrometry. You will learn how to operate and optimize performance of the laser equipment and high vacuum systems, and assist with the raw data collection, processing and analysis. A student curious about the intersection of fundamental physical chemistry and chemical engineering is especially welcome to apply. This position is for Fall/IAP with potential for a longer term commitment.

Prerequisites: Good communication and time management skills are required. A basic understanding of chemical kinetics and physical chemistry principles is desired. Some familiarity with MATLAB is preferred. Previous experience working with gas flow systems and/or aligning laser optics is a plus. A time commitment of at least 8 hours a week is required.

Contact: Dr. Mica C. Smith (mcs@mit.edu)


11/9/18

Term: IAP/Spring/Summer

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

MIT Faculty Supervisor Name: Christopher Knittel

Project Title: Uncovering the discrepancies in estimates of compliance costs with fuel economy standards between the 2016 TAR and the 2018 NPRM

Project Description: Following the Energy Independence and Security Act of 2007, the Environmental Protection Agency (EPA) and National Highway Traffic Safety Administration (NHTSA) set fuel standards to achieve a fleet-wide fuel economy of 35 mpg by 2016, and a projected 27 to 55 miles per gallon between 2012 and 2025. As part of the 2017-2025 standards issued by the agencies in 2012, the EPA and NHTSA were required to conduct a midterm review of the fuel economy improvements affecting model years 2022-2025. The 2016 technical assessment report (TAR) concluded that these 2022-2025 standards were technologically feasible, and that benefits far exceeded costs.

Recently, the Trump Administration in a 2018 Notice of Proposed Rulemaking (NPRM) finds that the costs of these Obama-era standards now exceed benefits, and proposes to freeze them at model year 2020 levels through 2025.

In relation to the 2016 TAR, while the 2018 NPRM reports overall lower benefits, the major substantial change comes from the estimation of the costs of compliance with the standards. Specifically, compliance costs with the corporate average fuel economy (CAFE) standard are 2.8 times higher in the 2018 proposal than the 2016 NHTSA analysis (and, in turn, even in the 2016, NHTSA projected compliance costs 2.6 times higher than the simulation models used by the EPA). And compliance costs with the GHG emissions standard are 7.5 times higher in the 2018 proposal, an increase from $35 billion in the 2016 TAR to $253 billion in the 2018 NPRM.

The purpose of this project is to uncover the discrepancies that drive the differences in estimates of compliance costs with fuel economy standards between 2016 TAR and the 2018 NPRM.

Full description of the project proposal can be found here: http://ceepr.mit.edu/files/UROP/2018-11-6-Knittel-UROP-fuel-economy-standards.pdf

Interested students should send their resumes and a writing sample, if available, to ceepr@mit.edu.

Prerequisites : We are looking for UROP students seeking credit or a stipend (paid position), with a strong preference for students who would like to commit to at least 2 semesters of work, or more (starting date is flexible). Ideal candidates would be responsible, motivated and detail-oriented and would be able to spend at least 8-10 hours a week on the project.  The project may also involve writing reports for the topic above and other projects that may fit. Basic programming skills, especially in R and Matlab  are required.

Relevant URL: http://ceepr.mit.edu/research/projects/UROP

Contact: Tony Tran (ceepr@mit.edu)


11/9/18

Term: IAP/Spring/Summer

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

MIT Faculty Supervisor Name: Mei Hong

Project Title: Investigation of structure determinants of cholesterol binding to an influenza virus protein

Project Description: This project aims to elucidate the molecular structural basis of influenza virus budding from host cells, in the quest to develop new antiviral therapies against flu infections. Specifically, the influenza membrane protein M2 binds cholesterol to cause virus budding and release. Disabling M2 cholesterol binding may thus be a new route of antiviral drug design. The project will involve synthesizing, purifying, and characterizing M2 peptides with various mutations in order to identify which sequences disable cholesterol binding. The student will have the opportunity to learn a broad range of skills, including organic synthesis, molecular biology, yeast culture, membrane biochemistry, and NMR spectroscopy. Work will be conducted at the Hong Lab in the Francis Bitter Magnet Lab (NW14) with a multidisciplinary team of chemists, biochemists and physicists.

Prerequisites: We seek motivated students with a strong curiosity about biomedical questions. Prior experience working in a laboratory and basic knowledge about protein biochemistry are required.

Relevant URL: http://meihonglab.com/

Contact: Mei Hong (meihong@mit.edu)


11/9/18

Term: Spring/Summer

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

MIT Faculty Supervisor Name: Sumanth Kaushik

Project Title: Infrared Polarization, Astrophysical Dust, and Star-formation

Project Description: Polarized light is one of the few ways of remotely measuring magnetic fields and has implications for many fields of astrophysics including studies of the solar wind, star-formation, and the cosmic microwave background.  It is not well-understood how the polarized light traces magnetic fields, or in what types of physical environments the correspondence fails.  The current project will use new far-infrared data to study the dust-induced polarization in regions of active star-formation and compare it to other data sets tracing temperature, density, and interstellar chemistry.

Data sets that might be examined include (but are not limited to) polarization of starlight and emission from Galactic clouds, photometric imaging, and spectroscopic observations from several space- and ground-based observatories. Duties may include identifying relevant data sets, calibration of raw data, assisting in generation of computer models.

Prerequisites:

  • Programming experience in C/python/matlab/IDL or equivalent
  • Strong interest in Physics and/or Astronomy
  • Physics I and II (8.01x and 8.02x), or equivalent
  • Past or concurrent intro Astronomy course preferred (e.g., 8.28x)
  • Student in 2nd-year undergrad. or beyond, preferred
  • U.S. citizenship per LL security requirements

Relevant URL: https://sofia.usra.edu/public/news-updates/first-images-demonstrate-capabilities-sofia%E2%80%99s-new-instrument

Contact: John Vaillancourt (john.vaillancourt@ll.mit.edu)


11/9/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Stefanie Shattuck-Hufnagel

Project Title: Acoustic analysis of speech cues

Project Description: UROP team project in speech analysis, IAP and Spring term Interested in the links among speech signal processing, linguistics and human speech recognition?  Have some background (or strong interest) in either phonetics/phonology, computer science or cognitive science?  In this UROP you will learn to label the individual cues to speech sounds in the speech signal by hand, to create a database for evaluating a prototype automatic speech analysis system that is in development. In the process you will learn to recognize the many ways in which a word or sound can vary in different contexts, and why this is important for understanding human speech processing, as well as for improving automatic speech recognition systems, and potentially designing interventions for speakers who are experiencing speech difficulties due to disease, injury or developmental delay. 

The position involves 20 hours per week of training during the 4 weeks of IAP, and then 10 hours per week during the spring term, applying the training to labelling the acoustic cue patterns in samples of speech from many different speakers and several different domains.  Possibility of advancing to coding modules for the developing speech analysis system, in the later stages of the project.  Pays $12 per hour.  Contact Dr. Stefanie Shattuck-Hufnagel, sshuf@mit.edu

Prerequisites: Suggested: interest in or background in phonetics/phonology, computer science or cognitive science

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


11/9/18

Term: Fall

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

MIT Faculty Supervisor Name: Prof. Tayo Akinwande

Project Title: Modelling and Characterization of Silicon Nanowires and Silicon Field Emitter Arrays

Project Description: In this work, we are developing low voltage, high current density and reliable nanostructures based on Si field emitter arrays primarily for nano-vacuum channel transistors and nano-focused X-ray sources. To achieve this, we are fabricating high aspect ratio nanowires with integrated nano-tips, and incorporating an additional gate for electron beam focusing. We are also working on the fabrication and characterization of electron transparent structures such as graphene above the gate to potentially improve the lifetime in poor vacuum environments.

In this project, we have opportunities for several students to carry out the following tasks:

  1. Modelling and/or characterization of the thermal effects of Si nanowires and emission properties of large area density Si FEAs with Silvaco;
  2. Modelling electron transmission through a graphene membrane using COMSOL Multiphysics;
  3. Characterization and analysis of fabricated FEA tips in an ultra-high vacuum system; and
  4. Assistance in designing and assembly of a compact system for nano-focused X-ray emission.

Through this research project, the students will be able to gain insights on device physics and electrical characterization techniques for various applications using Si FEAs.

Contact: Girish Rughoobur (grughoob@mit.edu)


11/9/18

Term: IAP/Spring

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Hugh Herr

Project Title: Neural Interfaces for Sensory and Motor Function

Project Description: Current limb prostheses for amputees do not allow one to control their limbs with their native neural signals. Non-invasive sensors have been developed to provide a control system, but none are highly sensitive. The biomechatronics lab is currently developing implantable devices to pair with a novel surgery that will enable patients to directly control prostheses and receive proprioceptive feedback. This project will involve the mechanical and electrical development of neural interfaces, their surgical implantation and testing. We will be performing surgeries in rats or mice, stimulating muscles and recording nervous signals. Then, we will characterize the muscular remodeling and physiological changes using histology and other techniques. For this multidisciplinary project, work will take place in the Media Lab and animal facilities with a team of mechanical engineers, biomedical engineers, electrical engineers, and clinicians. UROP will perform a variety of roles and learn medical device development, data collection and analysis as well as scientific writing.

Prerequisites: Previous experience with animal work, immunohistochemistry, or electronics would be very helpful - but not required.

Relevant URL: https://www.media.mit.edu/projects/electrical-interfaces/overview/

Contact: Shriya Srinivasan (shriyas@mit.edu)


10/31/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Prof Ann Graybiel

Project Title: 2-photon calcium imaging of neuronal activity in a mouse model for Parkinson’s disease

Project Description: The striatum is a brain structure that is critical for motor control, motivation and learning, and is strongly implicated in neurodegenerative diseases. More than 4 decades ago it was discovered that the striatum is composed of multiple different compartments, the striosomes and matrix, and evidence from post-mortem studies suggests that these play an important role in neurodegenerative diseases. We have developed a method for recording from both compartments in mice and we are now able to, for the first time, record and manipulate the activity of these compartments in awake, behaving mice. We have set up a behavioral task that investigates aspects of behavior that are affected in Parkinson’s disease, to test what role the striosomes and matrix play in controlling these behaviors. We are looking for students to help us perform these experiments. The undergraduate student will be responsible for working with the mice, performing behavioral tests in combination with optogenetic manipulations, performing immunohistochemistry and helping to analyze the data.

Prerequisites: Please provide details on any We are looking for a highly motivated student who is enthusiastic and eager to learn state of the art neuroscience methods. Work will take between 9 and 14 hours a week. We prefer students that are looking to be part of our team for multiple semesters.

Contact: Bernard Bloem (bbloem@mit.edu)


10/30/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Leslie Kaelbling, Tomas Lozano-Perez

Project Title: Learning for human-in-the-loop planning in robotics

Project Description: It is well-understood that in order for robots to function in the real world, they must be able to execute tasks over long time periods while in the presence of or under the supervision of a human. Even in a static environment, a robot should be able to plan out how it will act in the world, but also be willing to change its plans based on events such as intervention or information by the human. We would like to build a system that learns from data/experience how to plan efficiently and resourcefully, given that a human is in some way involved in the environment or task.

Student: Rohan Chitnis, ronuchit (at) mit (dot) edu

For more information, concrete project suggestions, and exercises to determine if you'd be a good match, please refer to this PDF: http://lis.csail.mit.edu/ronuchit/UROP_Proposal_and_Exercises.pdf. Send me an email if you're interested, or if you have your own project idea you want to pursue together!

Prerequisites: Please try the exercises in this PDF: http://lis.csail.mit.edu/ronuchit/UROP_Proposal_and_Exercises.pdf to determine if you'd be a good match.

Relevant URL: http://lis.csail.mit.edu/ronuchit/UROP_Proposal_and_Exercises.pdf

Contact: Rohan Chitnis (ronuchit@mit.edu)


10/29/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Professor Stuart Madnick

Project Title: Evaluating Effectiveness of an Embedded System Endpoint Security Technology on Energy Delivery Systems:Defeating hackers of IIoT

Project Description: Cyber threats are becoming more common in our everyday lives. The attacks that are often mentioned in the news, generally talk about the most recent data breaches. A commonly overlooked but equally as vulnerable area is the industrial sector. Many industrial control systems are susceptible to attack through vulnerable IoT devices. Vulnerable devices can have cascading negative effects on an EDS if they are exploited, such as plant shutdowns or critical failures.

The goal of this project is to develop and determine the effectiveness of a software agent designed to run on industrial IoT devices. The agent running on these devices will be responsible for ingesting a whitelist of applications and network addresses. The agent will use the whitelist to determine what is allowed to run on the device and what other devices on the network it may communicate with. Implementing whitelists will allow us secure these devices by restricting how they function and what other devices they communicate with. Students will be doing market research on industrial cyber security products and offerings. The research hopes to find out what types of solutions exist to address cyber threats in industrial control systems.

Please email Matt Maloney (maloneym@mit.edu) with 1) your CV, and 2) a brief description of why you are interested in this position. Feel free to ask any questions.

Prerequisites: Required skills include attention to details, critical thinking, as well as excellent reading, writing, and communication skills. Familiarity with cybersecurity and or energy delivery systems is a plus but not required. We are particularly interested in working with motivated and organized students who are committed to doing research.

Please email Matt Maloney (maloneym@mit.edu) with 1) your CV, and 2) a brief description of why you are interested in this position. Feel free to ask any questions.

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

Contact: Matt Maloney (maloneym@mit.edu)


10/25/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Edward (Ted) Gibson

Project Title: Studying how the human brain and intelligent machines process language

Project Description: Language is the signature of human cognition: it is unique to our species (*only* humans have it); it is universal across cultures (*all* humans have it); and it is designed to efficiently transmit meanings from one mind to another, such that linguistic structures reflect the structure of our mind. Therefore, figuring out how language works is a critical step towards understanding “the stuff of thought”. This scientific enterprise is also essential for designing artificial intelligence: despite having Siri, Alexa, and Google Translate, even state-of-the-art intelligent machines are still rigid, fragile, and can be easily tricked or broken by sentences that humans have no problems with. So how do our minds achieve fast, robust, and flexible comprehension?

We are pursuing multiple projects aimed at determining the distinct mechanisms involved in language processing, the division of “mental labor” across them during comprehension, and their place within the broader architecture of the human mind:

Some projects examine how comprehension unfolds in our minds by studying how it engages our brains. Using functional MRI hypothesis- and data-driven analyses, we characterize networks of brain regions that are recruited when adult native speakers understand language: what is their internal organization? Which networks are distinct vs. overlapping? How do they each contribute to comprehension? And how is information integrated across them?

Other projects use computational methods to establish the format of linguistic representations that are generated by algorithms trained on natural texts (e.g., distributed semantic models or deep neutral networks). Which distinctions in meaning do these representations make more—or less—salient? What knowledge about words, their combinations, and the underlying concepts, is implicitly captured by these representations? Which features of the linguistic input are minimally required for machines to extract this knowledge? And how does this knowledge compare to benchmarks based on human behavioral data?

Duties: Depending on your interests and skills, you will join either some neuroimaging projects or some computational modeling ones. Your duties will include some combination of the following: helping to review the relevant literature and to design experiments; using machine-learning methods to analyze fMRI data; creating experimental materials, collecting behavioral data (through an online platform), and testing computational models against them. You will learn how to design experiments, how to use analytical tools to address questions in cognitive science, how to critically evaluate experimental data, and how to present research results.

Prerequisites: We are looking for for-credit UROP students, with a strong preference for students who would like to commit to at least 2 semesters of work, or more (starting date is flexible). Ideal candidates would be responsible, motivated and detail-oriented and would be able to spend at least 8-10 hours a week in the lab. Basic programming skills, especially in Matlab (and/or Python) are required; some knowledge of linear algebra is highly desirable. Coursework in cognitive science / linguistics is a plus but not required.

Contact: Evelina Fedorenko (evelina9@mit.edu)


10/25/18

Term: Fall/IAP

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Kent Larson

Project Title: Human detection and human interaction recognition in videos

Project Description: The goal of this project is to use current state-of-the-art techniques computer vision (scene understanding) to recognize, in video data, interactions among people. The work involves the implementation and evaluation of deep learning models. In particular, the data of this project are street views and indoor views. This is an excellent opportunity to learn about the latest deep learning for visual recognition, both for object detection (people detection in particular) and also for higher level visual recognition, like human interactions.  This project is contextualized in Deep Urban Interaction Project from City Science research group at MIT Media Lab. The project is aiming at understanding how people use public spaces and how urban interventions, such as adding a café or a landscape feature, will have impact on urban vibrancy, of which urban interaction is one of the key measurements. PhD student and research assistant Yan Zhang (‘Ryan’) will guide the student on a daily basis.

Prerequisites: PyTorch/TensorFlow/Keras

Relevant URL: https://www.media.mit.edu/projects/DUI/overview/

Contact: Yan (Ryan) Zhang (ryanz@media.mit.edu)


10/25/18

Term: Fall

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

MIT Faculty Supervisor Name: Mariana Aracaya

Project Title: Metrics of Urban Form

Project Description: The overall aim of this project is to construct urban form metrics using a combination of remote sensing and geospatial techniques. In particular, this project examines the persistence of urban form through the study of the first housing initiative: The United States Housing Corporation (USHC). The USHC planned more than one hundred new neighborhoods in twenty-four states. Surprisingly, we know very little about the location of these developments and how their built form has had a lasting impact on the social dynamics of their inhabitants.

This project is offering motivated students interested in computation and social sciences an opportunity to explore new approaches to measure the built environment. The goal of this study is to use CAD software to digitize neighborhood plans, to geocode them using GIS software, and to process satellite images and vectored plans to construct a series of built form metrics.

Prerequisites: The final deliverable will be a dataset containing the spatial metrics for each digitized neighborhood. The team is looking for someone that is excited about applying geospatial methods to study the built environment, and who is comfortable with statistics (though not required).  More importantly, we welcome MIT students excited about testing different  approaches, challenging ideas, and getting into the data.

Contact: Arianna Salazar Miranda (ariana@mit.edu)


10/24/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Benjamin Olken

Project Title: Stuck in traffic UROP (with transit.big.data)

Project Description: Interested to apply big data algorithms to urban transportation problems?

Improve your data skills while working on a real problem together with researchers and an urban transportation agency.

Background: Commuting in Jakarta, Indonesia, a region with 30 million inhabitants, is anything but easy. TransJakarta, the city’s bus-rapid-transit (BRT) system, is the largest in the world by track length, yet ridership is significantly lower than for other BRT systems.

Project. We are working together with TransJakarta (PT Transportasi Jakarta or TJ) to analyze and experiment with system improvements that would eventually boost ridership. We are studying bus bunching, bus scheduling, driver incentives, among other angles.

Data. We work with the trove of big data that is collected daily by TJ as part of their operations: minute-by-minute bus GPS data, and passenger-level tap-in and tap-out data.

Challenge. Big data comes with big challenges. Your challenge is to build on powerful existing code in python to develop, test and implement a suite of tools to automatically process raw GPS and passenger ticket data. This includes algorithms to snap points to the bus route network and detect outliers, and manually cleaning network route data. At a later stage, we may start running bus simulations in a synthetic environment.

Prerequisites: We seek an exceptional UROP during IAP to make an important contribution to this project. You will work closely with the researcher team.

The ideal candidate:

  • Computer science or related.
  • Excellent python skills.
  • Ability to build on existing code basic familiarity with git.
  • Familiarity working with data is a plus.
  • Keen attention to detail and perseverance.
  • Interest in economics, transportation and/or urban issues is a plus.

To apply, email Gabriel (gabriel.kreindler@gmail.com) with subject line “[RA transit big data]” with a CV and a short paragraph describing your python experience and working with data (courses and projects), and an unofficial transcript.

Contact: Gabriel Kreindler (gabriel.kreindler@gmail.com)


10/24/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Rosalind Picard

Project Title: Video analysis for mood and personality trait recognition.

Project Description: The goal of this project is to test current state-of-the-art techniques for mood and personality trait recognition on video data recorded during a human-robot conversation. The work involves implementation and evaluation of the models developed in the affective computing group. The developed models are going to be integrated in an emotionally intelligent social robot for emotional wellness. This is a great opportunity to learn about latest machine learning (deep learning in particular) and affective computing in a practical application. This project is part of the MIT Advancing Wellbeing Initiative and the MIT Quest for Intelligence (QI).

If you are interested in this position please state your background/experience, major, class year, and why you are interested in the project in the response. Dr Agata Lapedriza will guide the student on a daily basis. We assure you that the work you do will be both rewarding and fun!

Prerequisites:

  • Matlab -- working level
  • Python -- proficient (previous experience of working with Pytorch or Tensorflow required)
  • Machine Learning -- intermediate level and above
  • Familiarity with Computer Vision
  • Estimated hours per week: 8-12

Contact: Agata Lapedriza (agata@mit.edu)


10/24/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Rosalind Picard

Project Title: Scene and object recognition for scene context analysis

Project Description: The goal of this project is test current state-of-the-art techniques of scene recognition, object recognition and visual attribute recognition on data acquired with a robot. The work involves implementation and evaluation of the models. The recognition of visual attributes will be focused on affect recognition techniques developed in the affective computing group. The developed models are going to be integrated in an emotionally intelligent social robot for emotional wellness. This is a great opportunity to learn about latest machine learning (deep learning in particular) and computer vision in a practical application. This project is part of the MIT Advancing Wellbeing Initiative and the MIT Quest for Intelligence (QI).

If you are interested in this position please state your background/experience, major, class year, and why you are interested in the project in the response. Dr Agata Lapedriza will guide the student on a daily basis. We assure you that the work you do will be both rewarding and fun!

Prerequisites:

  • Matlab -- working level
  • Python -- proficient (previous experience of working with Pytorch or Tensorflow required)
  • Machine Learning -- intermediate level and above
  • Familiarity with Computer Vision
  • Estimated hours per week: 8-12

Contact: Agata Lapedriza (agata@mit.edu)


10/24/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Robert Langer

Project Title: Development of novel therapeutics for cardiovascular disease

Project Description: This project aims to develop novel therapy for heart drug delivery in the fight against cardiovascular disease.  Specifically, this involves the application of a number of novel cellular models to screen our proprietary screen . The project is at the forefront of drug development and novel chemical synthesis and will delve into the basic biological mechanisms of cellular interaction upon drug delivery. This project involves a variety of skills: Tissue culture, molecular biology, bioinformatics and ultimately in application within in vivo. Work will be conducted in the Langer Lab in the Koch Building in collaboration with a multidisciplinary team composed of chemists, material scientists, mechanical engineers, chemical engineers, and physicians. 

Prerequisites:

  • Skilled in at least one programming languages (Java, Python, R, Matlab, etc).
  • Basic biology training and thirst for biological knowledge and curiosity.
  • Familiar with basic concepts of molecular biology
  • Comfortable in basic computational analysis on R.

Contact: Dr Rameen Shakur (rshakur@mit.edu)


10/22/18

Term: Fall

UROP Department, Lab or Center: Operations Research Center

MIT Faculty Supervisor Name: Georgia Perakis

Project Title: Learning, Optimizing and Impacting the Operations of a High Fashion European Retailer: From Theory to Practice

Project Description: This project focuses on real world applications of demand learning and operations optimization for one of the largest fashion retailers in Europe. We will be working with our European partner to fundamentally impact how retailers think about demand for high fashion. The project will give the opportunity to work with real world data and give better understanding of the challenges researchers face when utilizing information provided by industry partners. This project will provide the chance to implement cutting edge machine learning with a focus on creating true impact in the company’s operations. Utilizing the predictions of the machine learning models and developing optimization methods, we aim to fundamentally improve the company’s decision process around their distribution network. Finally, the project will drive towards a pilot with continent-wide scope that has the possibility of changing international operations. 

Responsibilities: First of all, you will be a full member of the research team and the whole team will meet weekly. In these meetings we will work on modelling the problem, devising algorithms, building theory, discussing results, and setting further steps. Outside of research meetings, we will work with data, implement and test algorithms, and research literature. The most important responsibilities will be to process the data, code the algorithms, and run the computational experiments that are decided upon during meetings.

Qualifications:

  • Experience with either Python, Julia, R, Matlab, or equivalent programming language is required
  • Experience with SQL is necessary

Contact Information: Please send applications or questions to Professor Georgia Perakis (georgiap@mit.edu), Tamar Cohen PhD student (tcohen@mit.edu), Yiannis Spantidakis PhD student (yspant@mit.edu) and Leann Thayaparan MBAn student (lpgt@mit.edu). Applications should include your resume and a concise statement of your interest, and why you would make a good fit. Second, third or fourth year students will be given preference. 


10/22/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Mriganka Sur

Project Title: Automated alignment of brain images to a common-coordinate framework

Project Description: A UROP research opportunity is available in the Sur lab for students who have a strong background in machine learning techniques and are interested in neuroscience research. Students will be involved in the development of an automated alignment toolkit which maps newly acquired brain images to the Common Coordinate Framework provided by the Allen Brain Atlas. This toolkit is critical for future anatomical studies of the brain as it will help speed up the registration and alignment process, which traditionally requires users to scroll through hundreds of slices in the template and manually resize images. Students will also have the opportunity to learn about techniques used in studying the anatomy and function of the brain, as well as interaction between brain areas.

Prerequisites:

  • Familiarity with machine learning and image processing techniques.
  • Experience with MATLAB is recommended but not required. Neuroscience background is not required.
  • Enthusiasm and interest in the project.

Contact: Nhat Le (nmle@mit.edu)


10/18/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: John Reilly

Project Title: Creating a Graphical User Interface for Energy-Economic Model

Project Description: The MIT Joint Program on the Science and Policy of Global Change combines scientific research with policy analysis to study the interactions among human and Earth systems to explore future climate, energy, food, water, air pollution and other interwoven challenges. Our main modeling tool is the Integrated Global System Modeling (IGSM) Framework, which combines an earth system model with a global energy-economic model.

We are in search on a UROP to create a graphical user interface (UI) for our energy-economic model that will help others access, visualize, understand and dig deeper into our model results. It will allow people to explore different policy scenarios, such as those related to the Paris Agreement. We believe such a UI will be a valuable communication tool for important insights about energy, the economy and policies.

This project is a great opportunity for undergraduate students to gain experience building UIs and improve their coding skills, while also learning about the kind of research we do.

Expected hours are 8-12 per week.

To apply, please email Jennifer Morris (holak@mit.edu) your current resume and a short message explaining your interest in the project.

Prerequisites:

  • Experience with designing user interfaces, or willingness to learn
  • Prior coding experience (python, R, etc.)
  • Background in computer science, data science or similar

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

Contact: Jennifer Morris (holak@mit.edu)


10/18/18

Term: Fall

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 lab/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 designing predictive models that capture bidder behavior on the platform.

Tasks for UROP:

  • A) Run machine learning models to understand bidder and farmer behavior on the platform.
  • B) Help in running online experiments to test updated auction designs for the platform.

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)


10/18/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Harvey Lodish

Project Title: Interrogating blood development to develop novel therapies for human disease

Project Description: We are seeking an undergraduate interested in learning bench lab techniques in molecular biology and genome engineering to help study the process of blood cell development as it relates to a variety of human diseases.  The undergraduate will be directly mentored by an MD, PhD physician scientist performing postdoctoral research in the Lodish laboratory, and will eventually work to identify novel targets suitable for genome engineering or signaling pathway manipulation as a means to treat human diseases of blood cell development.

Contact: Hojun Li (hojun.li@wi.mit.edu)


10/18/18

IAP and beyond

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

Faculty Supervisor: Ann Graybiel

Project Title: Neural circuit degeneration in mouse models of Parkinson’s disease

Project Description: We are seeking a student to help full-time over IAP and with continuation during the academic year for credit. The research involves histological and behavioral studies of mouse models of Parkinson's disease. Parkinson’s disease is characterized by the loss of dopamine-producing neurons, which leads to reduced motivation and movement. With new transgenic mouse models, we have been able to identify, for the first time, unusually strong connections among a distinct subset of dopamine-producing neurons. We have now discovered that these connections are lost in mouse models of Parkinson’s disease. We seek students to further this research by testing how and when these specialized connections degenerate, by immunohistology of brain sections in transgenic mice. We will further examine the motivation to complete motor tasks in mice that have abnormalities in these striato-nigral connections.

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: None

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

Contact: Jill Crittenden: jrc@mit.edu


10/11/18

Term: Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Kent Larson

Project Title: CityScope Developer

Project Description: The City Science group at the MIT Media Lab is looking to hire one or two students to assist with the development of tools for an upcoming. The CityScope tool has been revised to fit a new, conformable, and portable table - called the Bento Scope. The UROP will help to build and implement software into the Bento Scope.

Prerequisites:

  • Superb Rhino & Grasshopper skills 
  • CAD/CAM, CNC, fabrication 
  • Python/JS a plus 

Relevant URL: https://www.media.mit.edu/projects/cityscope/overview/

Contact: Margaret Church (mdchurch@media.mit.edu)


10/10/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: William H. Green

Project Title: Modeling of fuel-rich natural gas combustion and polycyclic aromatic hydrocarbons (PAHs) formation

Project Description: Recruiting for the Aromatics sup-group in the Green group. With the development of efficient production methods for shale gas in early the 2000s, and the consequent fall in price, there has been increased interest in converting natural gas into chemicals. In Green group, there is a modeling project focusing on industrial applications of natural gas. Accurate prediction on the production of valuable chemicals and polycyclic aromatic hydrocarbons (PAHs) is targeted. By using a software developed in Green group, Reaction Mechanism Generator (RMG), chemical mechanisms are built based on ab-initio quantum chemistry calculations and experimental data. In this work, how to transform literature data into kinetics and thermochemistry properties, and apply them into real-world processes are the first priorities.  Currently, a decent model up to 3-ring aromatics (C12 chemicals) has been developed, so the future direction is to expand the size of predictable molecules.

Prerequisites: This position is aimed at people with good communication skills and a strong motivation for working with and applying chemistry insight into combustion. Please include details of previous research experience and academic interests when applying.

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

Contact: Jim Chu (jimchu@mit.edu)


10/10/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: John Guttag

Project Title: Identifying and Mitigating Disparities in Cardiovascular Care

Project Description: The GRACE score estimates the risk of a patient to suffer an adverse cardiovascular event (like heart attack), based on a small number of measurements that are available upon or soon after hospital admission. However, we know there may be disparities in the way that men and women are diagnosed and treated, and in fact we have observed that the GRACE score is more accurate for the male population.  This project is a deeper investigation into this performance disparity, potentially also building a better risk score.  Some questions you can explore include: Are there different features that are more or less effective for men vs women?  Do the characteristics of these two populations differ in some important ways? Are there other models we could design (e.g., a multitask model or special regularizers) to pay attention to the appropriate features and ensure good performance across both groups?  How would these methods compare to building separate models for different groups?

Prerequisites: Some coding experience (ideally python + packages like sklearn/pandas) and ML/data science knowledge

Contact: Harini Suresh (hsuresh@mit.edu)


10/9/18

Term: Fall

UROP Department, Lab or Center: Architecture (Course 4)

Project title: Solar Powered Drones for Environmental Conservation II

Project Description: In this project we continue the development of a solar powered flying drone for conservation purposes. During the summer, the team has assembled a first prototype of such a drone, christened BluDart I and has traveled to Peru to test the drone on the ground in the area for which it was intended. 

In the second phase of the project we will focus on the main challenges that were identified for improving drone operation in phase one. These challenges are:

  • I. Improving the solar / battery system to increase charging efficiency and resilience
  • II. Optimize the drone for lower power consumption by making it lighter, more aerodynamic and using low power motors.
  • III. Improving the sensor system to extend its scanning capacity, for example by using LIDAR

By the end of the project there should be a second version of the drone – BluDart II – which can demonstrate operational independence over several days with battery recharging and the capability to follow a course. Additionally, the drone should be able to perform measurements (optical, acoustic,…) at defined times. As an extension we will look into designs for drone types other than quad-copters for continuous surveillance. The project will be carried out in close collaboration with Conservation International. 

We are looking for up to two additional UROPs on this project. Applicants should have experience with drone building and flying or working with solar cells and batteries. 

Contact: For more information please contact Ian Marius Peters (impeters@mit.edu).


10/9/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Leslie Kaelbling

Project Title: Integrating Deep Learning and Algorithmic Planning

Project Description: We aim to integrate model-free deep learning and model-based algorithmic reasoning for robust robot decision-making under uncertainty. The key to our approach is a unified neural network representation of the robot policy. This policy representation encodes both a learned system model and an algorithm that solves the model, in a single, differentiable neural network.

In this project you would investigate important research questions related to the combined learning- planning approach: 1) how do we transfer learned models from a simulator to a real robot? 2) which algorithms can be encoded in a neural network? 3) what robotic tasks can we solve by integrating learning and planning?

Prerequisites: Familiarity with deep learning libraries and/or planning algorithms is preferred.

Relevant URL: lis.csail.mit.edu/new/opportunities.php

Contact: Peter Karkus (karkus@mit.edu)


10/5/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: William H. Green

Project Title: RealTherm: A Thermodynamic Property Estimator for Real Gases

Project Description: Our group is developing the Reaction Mechanism Generator (RMG) software (see rmg.mit.edu) that automatically constructs chemical kinetic models to predict the time-evolution of species for a wide range of chemical systems (e.g., from fuel to drug oxidation). The RealTherm project focuses on developing a standalone software that estimates thermodynamic properties at arbitrary temperature and pressure, taking into account deviations from ideal gas behaviour. Using RealTherm a user would be able to assess the likelihood of a process to occur at the desired physical conditions. You would be working with us to develop this code, interfacing with RMG.

Prerequisites: Python programming in a Linux environment

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

Contact: Alon Grinberg Dana (alongd@mit.edu)


10/4/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Prof. Vladimir Bulović

Project Title: Designing flexible solar cell module array deployment system to increase access to solar water pumping

Project Description: The GridEdge Solar Research program is a highly collaborative team of electrical/mechanical engineers, chemists, and materials scientists. The team is working toward design, manufacturing and piloting of lightweight and flexible solar cells to increase energy access in low-income communities. These solar cells have tremendous potential to provide energy services for low-income farmers who use solar energy for irrigating their fields. We are looking for someone to help with designing a system for deploying lightweight solar panels for solar water pumping applications. To be affordable, the system should be low-maintenance, easily retractable, and deployable multiple times in one day. The design work involves includes starting with basic sketches and prototypes and testing system robustness in the wind tunnel. Subsequently development of SolidWorks models and assembly of larger systems will be undertaken. If the project is successful, there will be the opportunity to travel to India, deploy the system and collect feedback from farmers. This project will involve several aspects of electrical/mechanical engineering and will be overseen and supported by our dynamic team of postdoctoral researchers and graduate students.

Prerequisites: (Can be learned as part of the position) Designing, prototyping and deploying electro-mechanical systems, developing understanding of customer needs and challenges with product usage, SolidWorks, machine shop, 3D printer, wind tunnel

Relevant URL: https://gridedgesolar.org/

Contact: Anurag Panda (apanda@mit.edu)


10/4/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Prof. Vladimir Bulović

Project Title: Durability of solar cells in mobile applications

Project Description: The GridEdge Solar Research program is a highly collaborative team of electrical/mechanical engineers, chemists, and materials scientists. The team is working toward design, manufacturing and piloting of lightweight and flexible solar cells to increase energy access in low-income communities. These solar cells have tremendous potential to provide energy services for low-income people whose livelihoods often require them to be mobile. We are looking for someone to help with testing and characterizing the impact of vibrations and shocks solar cells experience when placed on top of a vehicle that has to travel on rough roads. This includes starting with a literature search to understand what is known about this issue currently and testing solar cells available in the market. Since there is limited information about this topic, the project will likely culminate with a publication reporting the results to the broader community. This project will involve several aspects of electrical/mechanical engineering, materials science and computer programming, and will be overseen and supported by our dynamic team of postdoctoral researchers and graduate students.

Prerequisites: (Can be learned as part of the position) Understanding of solar cell physics, working with mechanical and electrical testing equipment and taking high quality measurements, possibly programming and automating testing equipment, current-voltage tester, vibration tester

Relevant URL: https://gridedgesolar.org/

Contact: Anurag Panda (apanda@mit.edu)


10/4/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Prof. Vladimir Bulović

Project Title: Designing a solar umbrella with integrated solar cells for street vendors

Project Description: The GridEdge Solar Research program is a highly collaborative team of electrical/mechanical engineers, chemists, and materials scientists. The team is working toward design, manufacturing and piloting of lightweight and flexible solar cells to increase energy access in low-income communities. These solar cells have tremendous potential to provide energy services for low-income people whose livelihoods often require them to be mobile. We are looking for someone to help with design and prototyping of an umbrella with flexible solar panels that integrates LED lighting, water-mist based cooling system and a cellphone charging port. This includes starting with basic sketches and prototypes and then developing SolidWorks models and assembling a deployable system. If the prototype is successfully developed, there will be the opportunity to travel to India, deploy the system and collect feedback from street vendors. This project will involve several aspects of electrical/mechanical engineering and will be overseen and supported by our dynamic team of postdoctoral researchers and graduate students.

Prerequisites: (Can be learned as part of the position) Designing, prototyping and deploying usable products, developing understanding of customer needs and challenges with product usage, various tools in the machine shop, 3D printer, SolidWorks

Relevant URL: https://gridedgesolar.org/

Contact: Anurag Panda (apanda@mit.edu)


10/3/18

Term: Fall

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

MIT Faculty Supervisor Name: James DiCarlo

Project Title: Automated Model Evaluation on Brain Recordings

Project Description: Our lab is developing Brain-Score.org , a large-scale competition for deep neural networks in neuroscience (akin to Machine Learning’s ImageNet). Models can be submitted to obtain a Brain-Score consisting of the model’s predictivity of neural measurements and human behavior. The best model then becomes the field’s best mechanistic guess as to how objects are recognized in the brain. We are hoping to scale this approach even further for which we need more automation.

Currently, model submission is manual: users send us an email, we give them access to the GitHub repository and they run their model locally. You would be working with us to automate this submission process. Similar to other frameworks (e.g. https://github.com/bethgelab/robust-vision-benchmark ), users would package their model in our submission framework which they can then submit to us via the website. Once we receive a model submission, our server would run the model on our benchmarks, store the results and notify the user.

Prerequisites: Necessary background experience:

  • Python 3
  • Linux
  • Some experience with backend web development

Optional background experience:

  • Django
  • Docker
  • Deep Learning Framework (PyTorch/TensorFlow/Keras)
  • Git version control

Relevant URL: brain-score.org

Contact: Christopher Shay (cshay@mit.edu)


10/2/18

Term: Fall

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

MIT Faculty Supervisor Name: Mark Bear

Project Title: Cellular mechanisms underlying stimulus response potentiation

Project Description: Stimulus response potentiation (SRP) is a robust form of learning in which mice learn to discriminate a familiar versus a novel visual stimulus over the course of 5-7 days. The potentiated response is expressed as an increase in the local field potential (LFP) recorded electrically in the deeper layers of binocular, visual cortex. However, we do not currently understand how this enhanced LFP is generated. To understand how the activity of different cell types contribute to the LFP, we are performing targeted in vivo patch-clamp recordings from fluorescently labeled cell types that are visualized using a two-photon microscope. This project will elucidate how the activity of individual cell types relates to the enhanced LFP and will shed light on the sites of plasticity that mediate SRP.

Prerequisites: Basic experience with Matlab. Experience in handling of mice is a big plus.

Contact: Ingrid van Welie (ivwelie@mit.edu)


10/2/18

Term: Fall

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

MIT Faculty Supervisor Name: Bradley D. Olsen

Project Title: Sustainable and Hydrophobic Protein-Based Materials

Project Description: Polymeric materials comprised of renewable biomass sources have great potential as alternatives to fossil fuel derived plastics.  Proteins are particularly interesting as feedstock for manufacturing engineering resins due to their unique propensity to aggregate and hydrogen bond to form hard materials.  In addition, the increase in demand for protein as materials valorizes underutilized protein-based waste streams in agriculture.  There are however, unique challenges in formulating these materials, as proteins are brittle and hygroscopic, and typically require large amounts of plasticizers and solvents to facilitate processing.  We have developed a strategy that allows protein-based resins to be processed and polymerized without the use of solvents by lowering melting points of proteins using surfactants.  The surfactants also function as compatibilizers, which allow addition of hydrophobic components to increase material resistance to humidity. Further studies on the effects of protein-surfactant interactions and nanostructure on material properties will contribute towards efforts to engineer materials for a sustainable future.

The UROP involved in this project will have opportunities to learn experimental skills including, but not limited to: high throughput formulation development, free radical polymerization, polymer processing, and materials characterization (tensile testing, rheology, x-ray scattering, microscopy).

Prerequisites: Students with an interest in chemical engineering, chemistry, and/or materials science are encouraged to apply. No prior lab experience is required, and training will be provided in all areas. We will give preference to candidates who can commit to working at least 10 hours per week during the academic year. We are offering academic credit for new UROPs.

Contact: Daphne Chan (wychan@mit.edu)


10/1/18

Term: Fall

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

MIT Faculty Supervisor Name: Ankur Jain

Project Title: Rules governing cellular RNA localization

Project Description: In project 2, students will study how the sequence of a RNA determines its cellular localization. The students will use molecular cloning, cell culture and live-cell fluorescence microscopy, and obtain training a variety of image analysis methods.

Contact: Beverly Dobson (bmdobson@wi.mit.edu)


10/1/18

Term: Fall

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

MIT Faculty Supervisor Name: Ankur Jain

Project Title: Understanding RNA self-assembly

Project Description: In this project, we will study how DNA and RNA can assemble into liquids and gels in a sequence dependent manner. We will investigate how certain disease associated mutations such as the ones observed in amyotrophic lateral sclerosis lead to misfolding and aggregation of RNA. Students will learn DNA/RNA preparatory and structure analysis methods, microscopy sample preparation, data collection and analysis.

Contact: Beverly Dobson (bmdobson@wi.mit.edu)


10/1/18

Term: Fall

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

MIT Faculty Supervisor Name: Asada

Project Title: Design, Fabrication and Testing of a Sawyer Robot Gripper

Project Description: Installation of wire harnesses is becoming increasingly complex and error prone, as modern products and systems become smarter, more complex, and more dependent on physical networks of wiring within control enclosures and platforms.

My research in the d’Arbeloff Laboratory for Information Systems and Technology, focuses on developing a novel robotic system that assists workers with wire harness installation.  The long-term goal of this project is to usethis robotic system to reduce errors as well as reduce worker fatigue andinjury during the installation process.

Two Sawyer Robots by Rethink Robotics are used for manipulating wires and collaborating with human workers. These robots are known for their use as collaborative robots for automation and industrial applications as well as their impeccable SDK for use by researchers. These two robots will be holding the wire bundles during the installation process and will be responsible for ensuring the wire is in the correct place for the worker to then install.

One key limitation of the Sawyer robots is that they only come with a few select end-effectors. Unfortunately, these OTS end-effectors do not meet the requirements of wire manipulation for this project. It is my hope that the UROP will be able to complete the initial design analysis and concept selection, fabrication, testing and implementation for a Sawyer-compatible end effector. This end-effector must be able to be attached to the Sawyer robot as well as be controlled via Python and ROS to open and close. Ideally, this end-effector will be able to sense the applied gripping force and will be able to apply enough force to prevent the wires from slipping.

Prerequisites

  • Must be comfortable with rigorous mechanical design (including use of Solidworks, picking mechanical components, etc.)
  • Experience using ROS preferred but not required. The UROP will learn ROS to implement their gripper.
  • Preferably a Junior or Senior who has already taken 2.007 and is either in or has taken 2.009. I believe this project will be (or at least can be) rigorous enough for use in an Undergraduate Thesis if desired.

Relevant URL: https://www.rethinkrobotics.com/sawyer/

Contact: Rachel Hoffman (rachelmh@mit.edu)


10/1/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Rafael Gomez-Bombarelli

Project Title: Machine Learning for chemical and biochemical design

Project Description: Conventional approaches to the optimization of small molecules and biological macromolecules such as proteins and nucleic acids are usually based in the manual exploration of a pre-defined search space. An initial set of samples is selected, they are synthesized and tested experimentally, and local optimization is performed, often by trial-and-error.

In this project, you will utilize artificial intelligence tools to learn structure-property relationships for drug molecules and sequence-property relationships for biological macromolecules. You will collaborate with experimental groups at MIT and use in-house data to predict biological activity of therapeutic candidates. In addition to structural information, you will use theoretical physics-based simulations like molecular dynamics to create rich features to learn from.

Furthermore, once the prediction tools are trained, we will apply generative models trained on the existing literature to automatically generate promising candidates that maximize biological activity, which will be tested in the lab.

Prerequisites: A combination of experience and interest in the following:

  • Python programming
  • Deep learning using pytorch / keras / tensorflow
  • Cheminformatics / medicinal chemistry / Bioengineering
  • Students from course 5, 6 and 10 are very welcome to apply.

Contact: Rafael Gomez-Bombarelli (rafagb@mit.edu)


10/1/18

Term: Fall

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

MIT Faculty Supervisor Name: Professor William H. Green

Project Title: Determining accurate thermochemistry and kinetic parameters of reactions using quantum mechanics calculations

Project Description: Prof. William Green’s research group focuses on developing accurate kinetic models to quantitatively predict the time evolution of chemical mixtures. The reliability of the kinetic model depends on the accuracy of the reaction mechanism, in particular the accuracy of the kinetic parameters for key elementary-step reactions. For the elementary reactions we are interested in, experimental data may not be available, and accurate measurements of kinetic parameters at the temperatures, pressures, and time ranges of interest may not be feasible. Therefore, in recent decades quantum mechanical (QM) calculations have become one of the most reliable ways to determine thermodynamic parameters of elementary reactions, in some instances exceeding the experimental accuracy. 

The popularity of using QM methods to complement experiments have increased due to easy to use software and program packages like Gaussian, Molpro, Orca, and Qchem. In Green group part of the research work is to automatically generate reaction mechanisms and determine highly accurate thermodynamic parameters of elementary reactions. We will use density functional theory (DFT) and coupled-cluster (CC) methods to determine thermochemical parameters. 

Current projects in Green group are related to the performance of proposed biofuels, the conversion of natural gas to valuable chemicals, the atmospheric chemistry of organic pollutants, energy-efficient and safe handling of sulfur contaminants, and the formation of carcinogenic pollutants in combustion. Further, the impact of determining these parameters are not limited to research in our group, they will also be used as benchmarks in the field of chemical kinetics and added to databases to use in future kinetic model predictions.

Prerequisites: Knowledge of general chemistry preferred. Experience in bash shell will be helpful but not required.

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

Contact: Professor William H. Green (whgreen@mit.edu)


9/28/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Edward Gibson

Project Title: Noisy channel language comprehension

Project Description: The language that we hear or read everyday is full of noise: people say/type the wrong word, conversations take place in loud rooms, and the listener isn’t always paying full attention. Yet, our brains are very adept at compensating for this noise so that, most of the time, we don’t even notice it! Come work in the Gibson lab and help conduct experiments to understand how our mind accomplishes this impressive feat.

Prerequisites: Experience with Javascript/HTML preferred.

Relevant URL: tedlab.mit.edu

Contact: Edward Gibson (egibson@mit.edu)


9/28/18

Term: Fall

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

MIT Faculty Supervisor Name: Professor Alan Jasanoff

Project Title: Investigate resting-state functional connectivity in the rat brain

Project Description: A UROP position is available in the lab of Prof. Alan Jasanoff in the Departments of Biological Engineering and Brain and Cognitive Science at MIT for the fall of 2018 and spring of 2019. Preference will be given to students who can commit to working in the lab for both semesters. No prior research experience is required or expected.

The goal of the project is to determine how the brain’s resting-state networks respond to a lack of peripheral sensory input. Components of the research involve animal surgery, brain imaging using fMRI, and data analysis. The UROP would be primarily involved in surgical and imaging experiments.

Primary responsibilities: The UROP will assist graduate student Sarah Bricault in the lab of Prof. Jasanoff in the some or all of the following:

  1. Surgically implanting cranial devices in rat brains (under supervision).
  2. Assisting with fMRI imaging of experimental animals.
  3. Assisting in the design, construction, troubleshooting, and use of relevant experimental systems.
  4. Other associated projects.

Contact: If you’re interested, please contact Sarah Bricault (sbricau1@mit.edu). Include a recent CV and a statement of interest.

Prerequisites: None

Contact Name: Sarah Bricault (sbricau1@mit.edu)


9/28/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Prof. Ron Weiss

Project Title: Engineered Living Materials and Shapes

Project Description: Looking for a design/architecture UROP to participate in an interdisciplinary project. In this ongoing project, we develop hybrid materials that combine the structural properties of cellulose, the main component of wood, with the living capabilities of a microbial biofilm. The resulting living materials are genetically engineered to self-heal, capture harmful chemicals, and adopt their properties.  In this portion of the project, we will grow cellulose biofilm into three-dimensional shapes using a unique fabrication process we developed that combines digital fabrication with biological growth. Priority will be given to students willing to continue working on the project during IAP and the Spring semester.

Prerequisites

  • Experience in Rhino, Grasshopper, and 3D printing
  • No prior experience in biology is required

Contact: Katia Zolotovsky (zolka@mit.edu)


9/28/18

Term: Fall

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

MIT Faculty Supervisor Name: Harry Asada

Project Title: Computational Modeling of 3D Cancer Cell Invasion into the Extracellular fiber network

Project Description: This project aims at significant advancement in quantitative understanding of 3D cancer cell invasion into the ECM fiber network. It will include cell-ECM interactions at the binding kinetics level and integrate the numerous key mechanisms into the modeling of whole cell-level migration. In vitro microfluidic experiments will be conducted to determine unknown parameters and verify the computational model. The resultant model will be used to predict how cell migration in 3D ECM is influenced by the stiffness and, also, ECM porosity, single fiber diameter, and cross-linker properties. It will be used to predict whether there is an optimal MMP (Matrix metalloproteinase) secretion level for 3D cell invasion into ECM; too much secretion of MMP rapidly degrades the ECM fiber network and makes it too soft, while too little secretion of MMP impedes the cell to invade into ECM. A group of cells can communicate with one another through stress and strain propagation in the ECM and create migratory behaviors as a collective event. The emergent behavior of collective cell migration will be predicted using the multi-scale computational model.

We are looking for enthusiastic and resourceful two UROPs to assist us with computational modeling of cancer cell invasion. The work will be conducted at d’Arbeloff Lab, under the supervision of Dr. Min-Cheol Kim and Prof. Harry Asada.

Prerequisites: Familiarity with solid mechanics, dynamics, and numerical analysis for solving ordinary / partial differential equations, but neither is strictly required. Experience in using Matlab, C++ programming, and Tecplot software would be great, but not necessary. The perfect candidates should be Senior undergraduate students.

Relevant URL: http://darbelofflab.mit.edu/computational-modeling-three-dimensional-ecm-rigidity-sensing-guide-directed-cell-migration/

Contact: Min-Cheol Kim (mincheol@mit.edu)


9/28/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Danielle Wood

Project Title: Human-Centered Artificial Intelligence Systems for Sustainable Development

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.

We are looking for a highly-motivated student with a strong interest at the intersection of artificial intelligence and human computer interaction for socio-economic development. The responsibilities include studying, designing, implementing, and evaluating AI powered social and mobile computing systems. The project is led by Neil Gaikwad, a doctoral student, and is supported by MIT-Sensetime Alliance on Artificial Intelligence, as part of the MIT Quest for Intelligence (QI) initiative.

This is a great opportunity to develop strong research skills and gain experience in the development of open sourced human-centered socio-technical system. The student will participate in the full research cycle — needfinding, design, web-based software implementation, and potentially publishing the results in a paper or poster in a top conference. The student may have the possibility to extend the project into the IAP/spring semester.

Prerequisites:

  • Experience and proficiency with either front-end web frameworks (React or Vue.js) or back-end web frameworks (Django or Node.js), or Both
  • Proficiency with Python, Javascript, Html/CSS, React, GitHub, and SQL
  • Recommended prerequisite coursework: 6.813/6.831, 6.148, 6.006 or similarexperiences at other universities/internships
  • Good to have: A web-based portfolio, familiarity with social computing systems research
  • Estimated hours per week: 8-12

Contact: Neil S. Gaikwad (gaikwad@media.mit.edu)


9/26/18

Term: Fall/IAP

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

MIT Faculty Supervisor Name: Domitilla Del Vecchio

Project Title: Measuring Resource Usage in Biological Circuits

Project Description: Resource sharing in biological circuits is a major problem causing poor predictability. We have developed a methodology for measuring the extent of resource sharing in biological circuits and are looking for a motivated student to help test and validate our methodology. As part of the UROP, you will learn about resource sharing in biological circuits.

Prerequisites: Bacterial cell culture experience preferred but not necessary

Contact: Cameron McBride (cmcbride@mit.edu)


9/26/18

Term: Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Andrew Lippman

Project Title: votoMosaic

Project Description: Why are you voting, and for whom? Join a team of Media Lab and Sloan grad students in building a visualization that encourages political organization and action. Akin to the Reddit r/Place mosaic, we automatically fill in tiles in a visualization based on photos uploaded by users.

Prerequisites: Prior experience building full stack web apps is required, more specifically React, web workers and Python. There will be a database component for storing a user's name, email, submitted image file and text. You will contribute to both back end and front end. Strong preference for juniors and seniors, not available for undergraduates.

Contact: Kalli Retzepi (kalli@mit.edu)


9/26/18

Term: Fall

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Mitch Resnick

Project Title: Programmable Video and Audio with Scratch Blocks

Project Description: The Lifelong Kindergarten group (LLK) aims to empower all children, from all backgrounds, to imagine, create, and share with new technologies. The group is most widely known for developing the Scratch programming language and online community for children.

This particular project in LLK focuses on developing a new tool for creating programmable video and audio projects on mobile devices. The tool utilizes the blocks-based programming technology developed for Scratch to allow kids and creators of all ages to quickly build complex audio-visual projects on tablet devices. An early demo of the video aspect of the tool can be seen at https://youtu.be/zaBsIfuv1IE.

For this project, we are looking for a student with significant technical skill in computer graphics and/or audio programming to help develop the tool. In terms of graphics skills, an ideal candidate would understand how to use a rendering pipeline in a multithreaded environment and would have some background working with a 3D API, like OpenGL. On the audio side, an ideal candidate would feel comfortable programming audio at the individual sample level and coordinate timing of audio output with video output. Most importantly, an ideal candidate would be a keen and eager learner who is willing to dive deeply into the technical weeds, push bytes around, and make some interesting things! The two main languages used in the project are Swift (for the mobile app and audio/video rendering engines) and Javascript (for the Scratch blocks interface and virtual machine).

This project is in an early and experimental stage so there may also be opportunities and ways to contribute to new aspects of the tool as well (e.g., a phone-optimized version, integration with other sensors on mobile devices, real time video mixing, among others).

Prerequisites:

  • [Required] A willingness to dive in and learn!
  • [Required] Background in programming at a low-level, ideally with realtime video and/or audio, in a multithreaded context
  • [Preferred] Experience with Swift, Javascript, and a graphics API (OpenGL, Direct3D, Metal, Vulkan, or similar)
  • [Preferred] Excitement about working with -- and making stuff for -- kids!

Relevant URL: https://youtu.be/zaBsIfuv1IE

Contact: Sean Hickey (hisean@media.mit.edu)


9/25/18

Term: Fall:

UROP Department, Lab or Center: CSAIL and Center for Gynepathology Research (Course 20 & Newton Wellesley Hospital)

Faculty Supervisor: Linda Griffith

Project Title: Establishing co-morbidities in gynecology diseases in a surgical practice using Natural Language Processing

Project Description: A UROP position is available to work with a team of clinicians (gynecology surgeons) collaborating with MIT to develop better methods of diagnosing and treating a common gynecology disorder, adenomyosis. Adenomyosis is characterized by the presence of endometrial lining in the uterine muscle, where it should not be located, and where it can cause excessive menstrual bleeding, pain, and infertility.  It has been difficult to diagnose and thus many patients go untreated.    Just recently, ultrasound imaging methods have been refined to evaluate the probability that a patient has adenomyosis. However, in many patients, the correlation between the ultrasound features of adenomyosis and their symptoms is lacking.  At Newton Wellesley Hospital, a large cohort of patients has been treated for painful periods in the past, but they were not specifically evaluated for adenomyosis as they were treated before the imaging metrics were available. In this project, the UROP student will develop a natural language processing (NLP) algorithm to mine electronic medical records (EMRs) of thousands of patients who have been treated in the gynecology practice at Newton Wellseley Hospital to identify patients with symptoms that are consistent with adenomyosis.  This will point to a set of ultrasound images that can be reviewed to see if they match the criteria for adenomyosis.  In a later phase of the project, specific features of ultrasound images will be analyzed to determine (a) a more automated method for diagnosis that could be implemented in the general gynecology practice and (b) if certain features correlate with specific symptoms, or specific responses to therapies.

  • Timeline:  UROP can start immediately. Project may extend into IAP/spring term for pay. Project is not very suitable for an M.Eng and no funding is currently available for M.Eng support.
  • Perks: Extensive interaction with clinicians is available in this project. Great experience for a pre-med looking for clinical exposure.
  • Social impact:  Adenomyosis afflicts up to 20% of women, starting even in teenage years, yet remains under-diagnosed, under-treated, and understudied.  This project will change the lives of millions of women by providing them and their caregivers information about their disease state, and will enable development of better therapies.
  • Supervision:  The project is jointly supervised by the Barzilay lab (Adam Yala), the Griffith lab (Griffith) and Dr. Megan Loring, a gynecology surgeon who carries out research at MIT 2 days per week.

UROP Position (credit or pay)

Requirements:  UROP must have experience with Machine Learning (e.g., have completed 6.036 or equivalent) and ability to work in a multidisciplinary team.

Contact: Linda Griffith (griff@mit.edu)


9/25/18

Term: Fall

UROP Department, Lab or Center: Edgerton Center

MIT Faculty Supervisor Name: Eric Verploegen

Project Title: Testing and Monitoring of Evaporative Cooling Devices for Improved Vegetable Storage in Low-Income Rural Communities

Project Description: We are looking for a student to help develop a testing chamber for low-cost evaporative cooling devices for improving vegetable storage in Africa and India. When affordable and effective post-harvest storage solutions are not available or affordable, people living in off-grid rural communities will often experience vegetable spoilage, loss of income, lack of access to nutritious foods, and large amounts of time spent purchasing vegetables. Evaporative cooling devices have the potential to provide a low-cost, local available, and effective solution for improving vegetable shelf life

The goal of the testing chamber is to identify how specific design variations impact the performance of the evaporative cooling devices and enable organizations that produce and promote these technologies to optimize designs for maximum performance and minimum cost. An Arduino based control system will need to be developed to regulate the conditions inside the test chamber, including sensors for measuring the performance of vegetable storage devices in the testing chamber.

The project will have potential follow-on travel opportunities to Kenya to use the sensor system to monitor the performance of evaporative cooling devices that have been installed in rural Kenya.

Interested candidates should email ericv@mit.edu with a brief explanation of why they are interested in this project and describe any relevant previous experience.

Prerequisites: Applicants should have an interest in practical solutions to global poverty challenges. Experience programming Arduino with is preferred.

Relevant URL: https://d-lab.mit.edu/resources/projects/evaporative-cooling

Contact: Eric Verploegen (ericv@mit.edu)


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)


9/13/18

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: 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)