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

12/7/18

IAP/Spring 

Department: Broad Institute

MIT Faculty Supervisor Name: Aviv Regev

Project Title: Learning CRISPR off-target effects and specificity

Project Description:  CRISPR/Cas9 and related proteins are increasingly important in both experimental science and therapeutic interventions. Cas9 (and other CRISPR proteins) are targeted to specific DNA locations by virtue of a complementary RNA guide. A central concern we have when using CRISPR proteins is (1) whether they will bind (and cleave) the DNA where we want them to, and (2) whether they will bind/cleave any undesirable locations, and if so, which. We are looking for a UROP to develop experimental techniques that will enable us to learn the rules that dictate what DNA sequence and RNA guide sequence combinations will result in DNA cleavage, under the supervision of a post doc and graduate student.

We will develop high-throughput assays to test combinations of guide RNA sequences and DNA sequences to generate the massive-scale dataset necessary for training the deep-learning models needed to predict when and where Cas9 will cut. The UROP will work closely with a postdoc and help with lab experiments and, if interested, can also help with the analysis of the resulting data. This opportunity can potentially transition to a research assistant position in the summer and beyond. Specific approaches that we will be using include: RT-PCR, CRISPR/Cas9, molecular cloning techniques, and high-throughput sequencing.

Specific end of UROP goal: You will develop and apply high-throughput genomic technologies for learning how sgRNA sequences target Cas9 to DNA.

Prerequisites: Previous experience with molecular biology techniques is recommended, but can also be learned by a motivated individual.

Contact: If you are interested in this position, please send an email to Carl de Boer: cgdeboer@broadinstitute.org and include:

• A resume/CV

• The number of hours you could work on the project per week

• A short description of why you are interested in working on this project

• Please put the title of the project in the subject line of your email

• Please indicate whether you are looking for IAP or spring or both IAP and spring, and whether you are seeking a UROP for credit or for pay.


12/7/18

IAP/Spring

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

MIT Faculty Supervisor Name: Pawan Sinha

Project Title: Game design to characterize dynamic object interactions in autism spectrum disorders

Project Description: Difficulty interacting with dynamic objects represents a salient, yet understudied, feature of the autism phenotype. These difficulties can present grave consequences for individuals with autism. Motivated by a theory we have proposed (Sinha et al., 2014), the overarching hypothesis guiding this project is that difficulties in interacting with moving objects may be an outcome of impaired prediction of the trajectory of moving objects as they unfold over time. In collaboration with the ActionLab at Northeastern University, this project aims to investigate these abilities across a range of motor tasks to test whether the difficulties seen clinically result from an underlying impairment in temporal prediction. The project uses gamified motor tasks to collect quantitative data regarding movement of individuals relative to objects in the environment. Deeper knowledge of these abilities holds relevance for adapting environments for children and adults with ASD, as well as for designing interventions that acknowledge and address potential underlying neurocognitive issues (e.g., prediction), and not merely the manifestation of the underlying impairment (e.g., difficulty in catching a ball).

Position Description: The primary responsibility of this UROP will be to contribute to the design of web-based games that engage school-age children. The student will work closely with others as part of a team, with substantial opportunity to work independently. This position is available for pay or credit.

Prerequisites:

  • The ideal candidate will have previous experience with digital game design, graphic design (e.g. Photoshop, Illustrator), and/or computer animation
  • Able to commit at least 20 hours per week during IAP and 8-10 hours per week during the semester.
  • Experience in graphic design, game interface design/testing, user interfaces, or related fields.
  • Ability to travel occasionally to Northeastern University for training or meetings desirable, but not required. (Northeastern is a 30 minute walk from MIT, and is also accessible via shuttle/public transport.)

Application and Deadlines: There is no application deadline for those who wish to volunteer. For direct funding* or credit, please refer to the UROP office deadlines. We recommend that you contact us at the start of the semester if you are interested, or at least several weeks in advance of the UROP deadline for which you wish to apply. We will begin reviewing applications on a rolling basis until the position is filled. Visit the UROP website for details about UROP requirements: http://web.mit.edu/urop/apply/deadlines.html

Contact: If you are interested in joining our team, please e-mail Annie Cardinaux, Project Coordinator at anniec@mit.edu, and include your Resume/CV/Portfolio and a letter describing your interest in and qualifications for the project. In your e-mail, please specify whether you would like to do the UROP for pay or credit.

*If you are selected and wish to complete the UROP for pay, you will need to create a project proposal for review by a member of our research team several days in advance of the relevant UROP deadline for that particular semester.


12/7/18

IAP/Spring

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

MIT Faculty Supervisor Name: Aude Oliva

Project Title: Crowdsourcing attention and memory with web and mobile

Project Description: The Computational Perception and Cognition Lab (http://cvcl.mit.edu/aude.htm) is looking for motivated undergrads with web dev experience to join the team and help develop interactive user interfaces for web and mobile, to record people's attention and memory performance on videos and graphic designs through a series of crowdsourcing perception/cognition experiments and games. Looking for students for IAP, Spring, and Summer. If interested, please send examples of past UI/web projects, GitHub repos, and CVs to: zoya@mit.edu.

Prerequisites: Required: proficiency with python, javascript, html, jquery.

Recommended: 6.148, 6.170 or similar.

Bonus: 6.036, 6.819, or similar.

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

Contact: Zoya Bylinskii: zoya@mit.edu


12/7/18

IAP/Spring

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Hiroshi Ishii

Project Title: Synthesis of novel biodegradable photopolymers for 3D printing

Project Description: Conventional stereolithography 3D printing uses acrylic-based monomers for polymerization. The presence of oxygen in the air prevents full curing on the surface of the print. Therefore, a post-curing process is always needed. This research deals with the synthesis and exploration of alkyne carbonate derivatives as biodegradable building blocks in the Thiol–ene photopolymerisation reaction to facilitate the 3D printing of dense microstructures. The Thiol-ene reaction offers higher rate of polymerization therefore eliminates the post-curing process

Your task will be synthesizing the photopolymer under instruction; reading literature research and iterate the design of the photopolymer, and characterize the photopolymer’s mechanical properties. The developed material will be used for a 3D printing fashion design, which will be featured in the Cooper Hewitt Museum in New York City in 2019.

Prerequisites: Experience in chemistry

Contact: Jifei Ou: jifei@mit.edu


12/7/18

IAP/Spring

UROP Department, Sloan School of Management (Course 15)

MIT Faculty Supervisor Name: Georgia Perakis

Project Title: Big Data and Online Platforms Analytics – Work with a Large Retailer in Latin America

Project Description: How competition and pricing strategies affect consumer behavior in online platforms? This project will combine two pieces: (1) Analyzing big datasets to model consumer behavior in competitive markets. (2) Running field experiments. We will use tools from machine learning, analytics, A/B testing, experimentation. This is a great opportunity to work in a fun and challenging research environment.

Responsibilities: (1) You will be a full member of the research team, and the team will meet weekly. (2) In the meetings we work on modelling, algorithms, discussing results, and setting up next steps. (3) The main responsibilities will be pre-processing data, coding algorithms (with our guidance), and analyzing data.

Qualifications:

  1. Some experience with Python and/or R and/or Stata is required
  2. Basic knowledge of Spanish is not necessary, but a plus.
  3. Available to start during IAP and Spring semester

Contact: Please send applications to Professor Georgia Perakis (georgiap@mit.edu), Diego Aparicio PhD student (dapa@mit.edu), Tamar Cohen PhD student (tcohen@mit.edu). Please email resume + a 2-sentence statement of why you are interested and a good fit for this project.


12/5/18

Spring/Summer

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

MIT Faculty Supervisor Name: Hazel Sive

Project Title: Understanding the Biochemical Changes in Neurodevelopmental and Mental Health Disorders

Project Description: We are utilizing multiple models to understand genetic contribution to neurodevelopmental and mental health disorders. We study the genetics in our zebrafish model and cell line models, and see how these genes contribute to the disease in patient stem cells. I am looking for someone that can contribute a small amount of time each day during the week, and help at times on the weekends. You will learn numerous techniques in molecular biology, biochemistry, cell culture, genotyping, fish behavioral assays, and more. Looking for an enthusiastic student for the Spring and Summer of 2019, and possibly staying in the lab through their time at MIT.

Prerequisites:

  • Biology
  • Beneficial to have taken a lab

Contact: Danielle Tomasello: dltom@wi.mit.edu


12/5/18

IAP/Spring

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

MIT Faculty Supervisor Name: Martin Hackl

Project Title: Child Language Development Research

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

UROP's main goals will be: engagement with cutting edge theoretical developments in language acquisition and acquiring hands-on experience with behavioral research with children. 

Prerequisites: Having taken 24.900 is preferred but not required. Given that the work is mainly about interaction with children and keeping them engaged in the experiments, you will have to be very good at playing with kids.

Contact: If you are interested, please email Prof. Martin Hackl (hackl@mit.edu), and also CC Leo Rosenstein (leaena@mit.edu) with your resume/CV. There are a few UROP positions for IAP 2018: Work hours are flexible. There is a possibility of continuing working in the subsequent semester(s). Applications received by Monday, December 24 will be given full consideration.


12/5/18

IAP/Spring

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

MIT Faculty Supervisor Name: Ezra Haber Glenn

Project Title: "Urban Planning in the News" case-bank/sourcebook

Project Description: The project seeks an undergraduate student with an interest in urban history, public policy, media studies, and/or journalism to help assemble an online case-bank and source-book of news stories for use in the "Urban Planning in the News" seminar. and related outreach.

Student(s) will research, collect, summarize, and organize news coverage (local and national; print and digital; news and commentary; left and right; contemporary and historical; etc.) tracing specific projects or controversies to illustrate and explore topics in urban planning, such as climate change adaptation; affordability and segregation; economic development and downtown revitalization; development of mass transit and transportation networks; race and policing; and other contemporary and historical debates.

For pay or academic credit.

Prerequisites: Strong writing and organizational skills; experience with online and library archival research, especially newspaper/magazines; interest in/familiarity with urban history and/or contemporary urban planning and policy debates; ability to be self-directed.

Contact: Ezra Haber Glenn: eglenn@mit.edu


12/5/18

Spring/Summer

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

MIT Faculty Supervisor Name: Zachary P. Smith

Project Title: Post-Synthetic Modification Techniques to Control Polymer Morphology for Gas Separations

Project Description: The ability to control the size distribution of free volume elements in a polymer membrane is of great interest for gas separations. In this study, functionalized polymer membranes will be post-synthetically treated to simultaneously remove functional groups and add free volume elements. By using this technique, specifically-sized free volume elements can be generated based on the functional group used. Currently, tert-butoxycarbonyl (t-BOC) is being used to functionalize a polyimide, and the gas separation performance of this newly-functionalized polyimide after post-synthetic treatment will be analyzed.  A variety of functional groups, as well as different polymer backbones, can then be used to determine whether this particular technique of post-synthetic treatment to precisely control the size and size distribution of free volume elements can be applied.  While this technique can be used for applications currently practiced with polymer membranes today, such as nitrogen enrichment, other emerging applications, such as hexane separations and small-molecule biopharmaceutical separations, can also benefit from polymer membranes with precisely controlled free volume elements.

Prerequisites: We are looking for students who have a strong interest in polymer science, chemical synthesis, and transport mechanisms. Prior chemistry laboratory experience is helpful but not necessary.  The time commitment will be around 5-10 hours per week during the spring semester.

Contact: Sharon Lin: sharonli@mit.edu


12/5/18

IAP/Spring

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Mike Bove

Project Title: Looking Sideways creative online exploration tool

Project Description: During IAP and Spring semester in the Media Lab’s Object-Based Media group, we’ll be continuing to develop computational design tools that embrace ambiguity and serendipity, vital for technologies used early in the creative process.  We’ll be refining the Sideways Search inspiration exploration tool (http://pathways.surge.sh/conceptnet/full/), an online browsing tool that seeks to provoke unexpected inspiration and guide pathways to new ideas through providing users with a selection of semi-randomly chosen, loosely related, diverse sources from art, design, history and literature for every search query.  We’ll be carrying out user studies and integrating that feedback into modifications of the tools, e.g. refining the UI and building new features.  There is also opportunity to work on the design(human)design tool (http://designhumandesign.media.mit.edu/), and help integrate these tools into a projection mapping table so that they can be viewed in a more immersive environment.

Skills required:

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

Contact: Philippa Mothersill: pip@mit.edu


12/5/18

IAP/Spring

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

MIT Faculty Supervisor Name: Francis O'Sullivan

Project Title: Techno-economics of energy storage systems

Project Description: Does the topic of energy storage fascinate you? Have you ever wondered about some of the business cases for advanced energy storage systems, especially in the context of a low-carbon energy future? If yes, we have some exciting ongoing projects that you could work on.

Project #1: Investigation of the techno-economics of hybrid systems using gas-turbines and advanced energy storage systems

We’re investigating the techno-economics of hybrid systems that employ gas-turbines together with advanced energy storage devices such as batteries. As renewables become a more prevalent source our energy in our society, our electrical grid will need to adapt accordingly to account for the variable nature of resources such as wind and solar PV. As the system transitions, conventional generators such as gas turbines often have to ramp up and down rapidly to address this variability and to make sure that the load is met. Such rapid ramps come at a cost to these systems in the form of efficiency losses and higher operational and maintenance costs. Can energy storage systems such as batteries, thermal storage or other chemical storage options play a role here by alleviating the need for these ramps and allowing the gas turbine to operate at more economical levels or are these storage options too expensive to provide such a service? Also, while storage may improve gas turbine operation, how does this integration affect the system as a whole? We’re using operational data from gas turbines to answer questions of these sort, which have significant real-world implications as we devise ways to address climate change more efficiently. We invite you to come be a part of our team.

Requirements:

  • Programming:
    • Fluency with Python
    • Modeling experience (preferred not required)
    • familiarity with processing modeling platforms like Aspen Plus or HYSYS (preferred not required)
  • Web Development (preferred not required):
    • Experience with Django
    • Fluency in PhP
    • Experience in web programming and database development

____________

Project #2: Techno-economic analysis of the costs of advanced energy storage systems: Energy Storage Technology Assessment Tool (ESTAT) Development

The project is on the development of a web-based energy storage technology cost/benefit assessment tool. Our research will examine the techno-economic tradeoffs between existing and emerging energy storage technologies. The initial framework as well as an online version of the tool has already been developed. The selected candidate will work on further developing the tool. In particular, and during the UROP period, we’ll seek to investigate hydrogen-based systems and flow batteries. This is a great opportunity to learn about advanced energy storage technologies and how to evaluate their costs and benefits. We are looking for someone with a background in chemical engineering, programming and ideally have web development experience. Detailed requirements listed below.

Requirements:

  • Some fundamental understanding of electrochemical energy storage systems
  • Programming:
    • Fluency with Python
    • Modeling experience (preferred not required)
  • Web Development (preferred not required):
    • Experience with Django
    • Fluency in PhP
    • Experience in web programming and database development

____________

Project #3: Development of a co-optimization model for energy storage with offshore wind

We are in the process of developing a decision-making framework that investigates the costs and benefits of advanced energy storage systems paired with offshore wind farms. The selected candidate will participate in advancing the development of the existing model. This is a great opportunity to learn about energy storage technologies and how to evaluate their costs and benefits, especially in the context of offshore wind farms. The experience gained can be put to use in similar decision-making frameworks and will be a useful skill to have. Detailed requirements listed below.

Requirements:

  • Familiarity with optimization techniques
  • Fluency/familiarity with Julia programming language
  • Some familiarity with electricity markets and services (preferred not required)
  • Some familiarity with energy storage systems such as batteries (preferred not required)

Contact: Apurba Sakti: sakti@mit.edu


12/5/18

IAP/Spring

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

MIT Faculty Supervisor Name: Douglas Hart

Project Title: Prototyping suction-based mechanism for underwater ROV attachment and locomotion

Project Description: Underwater remotely operated vehicles or ROVs for short, are used in many applications ranging from deep sea exploration to specific tasks such as inspection and cleaning of surfaces underwater. These surfaces could be on stationary structures such as tanks, pipes or oil rigs or moving structures such as ships, submarines, or even marine animals. ROVs typically use thrusters to maneuver underwater. For applications in high ocean currents or where a close distance is required between the ROV and the surface of interest, thrusters may not be the optimal solution. This research aims at designing, prototyping, testing, and validating a suction-based mechanism for ROVs so that they can attach to surfaces underwater and traverse them.

As a UROP you will get to be part of every element of the design process in which getting your hands dirty is crucial. If you are interested please reach out to me (acobi@mit.edu) asap so we can schedule a time to meet and discuss. Ideally the for-credit UROP would start immediately or at the beginning of IAP.

Prerequisites:

  • Machine Shop skills (lathe/mill/waterjet)
  • Rapid Prototyping skills (laser cutter/3D printer/hand tools)
  • Programming is a plus

Contact: Alban Cobi: acobi@mit.edu


12/3/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Steven Barrett (AeroAstro Department)

Project Title: High energy density battery prototyping for a solid-state ion airplane

Project Description: An interdisciplinary team from AeroAstro and EECS flew the first solid-state ion airplane, recently published in Nature (https://www.nature.com/articles/s41586-018-0707-9). Work is currently underway to develop a 2nd-generation aircraft which will be able to fly faster and for longer. High energy density energy storage is crucial for this new aircraft. We are seeking a UROP to undertake research of currently available battery technology and develop the battery pack to be used on the aircraft.

Prerequisites:

  • The student is required to have taken 6.002.
  • Some experience in electronics prototyping and battery systems would be very helpful.
  • The student is required to commit at least 10 hours a week.

Relevant URL: http://electricaircraft.mit.edu/, http://lae.mit.edu

Contact: Haofeng Xu (xuh@mit.edu)


12/3/18

Term: IAP/Spring

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 the entanglement mechanism.

Prerequisites: No experience required. We are looking for a highly motivated student who is enthusiastic about hands-on experiments and pays attention to details.

Contact: Beatrice Soh (bsoh@mit.edu)


12/3/18

Term: IAP

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

MIT Faculty Supervisor Name: Justin Steil

Project Title: Analyzing Eviction Dynamics

Project Description: Housing advocates and city officials are increasingly describing the eviction rate in Boston as a crisis.  Legal services lawyers and community organizers report intense displacement pressures in low-income, neighborhoods and in communities of color as these neighborhoods gentrify and rents rise.  Policy analysts and researchers also point out that as home values rise, higher income populations are remaining renters longer, resulting in a tightening of the rental market and an increase in rental prices.  Evictions appear to be widespread in low-income communities amidst these market changes.  Yet while there is near consensus that the rate of evictions is alarming, there is still much we do not know about the precise extent to which evictions are occurring, where they are occurring, and which individuals and/or communities are most vulnerable.

The goal of this project is to better understand the dynamics of eviction in Boston in order to more effectively design policy solutions and more appropriately target legal representation.  Our specific goals fall into two overarching categories: identifying the prevalence of displacement caused by eviction filings, by reviewing case files to identify cases in which tenants sign agreements to move out of their home, and; mapping who is most vulnerable to eviction, by reviewing case files to identify characteristics of the eviction filing, the legal procedure the case followed, of the property, and of the property owner to better understand who is able to remain in their unit after an eviction is filed and who ends up being formally evicted or agreeing to move out.

To gather initial data for this research we will first scrape available data from the MassCourts website, to obtain a count of eviction filings, party names, property addresses, etc.  We will then merge the eviction filing data with parcel level data about building types and property ownership from the City of Boston Assessing Department.

To obtain the data about the dynamics of each eviction, we will randomly select a total of 1,500 files spread across the years 2013 to 2018 and request those files from the Massachusetts Housing Court.  We will photograph each page of each of those files and then code each file systematically to identify the relevant details of each case, including: the type of eviction filing, the amount owed and time in arrears for non-payment filings, the outcome (default judgement, agreement for judgment, trial), the substance of any agreement for judgment (time to pay, etc), whether the defendant was represented by counsel, whether an answer was filed and discovery requested, whether affirmative defenses and counterclaims were asserted, and whether a jury trial was demanded.

Once the files are coded, we will merge them with the MassCourts data and the Assessing data to create a robust dataset regarding eviction dynamics. With those data, we will first be able to estimate the effective eviction rate by identifying the rough share of eviction filings that end in a tenant’s departure from the unit.  We will also be able to estimate time trends over the past five years and differences by neighborhood in completed evictions and move outs.  Second, we will conduct logistic regressions to estimate the relationship between completed evictions and move out agreements, on the one hand, and characteristics of the building, the landlord, the eviction filing and the procedural history to better understand who is most vulnerable to displacement as a result of an eviction filing.  It will also allow us to estimate what factors may protect against displacement and allow residents to remain in their homes.

We are looking for UROPS to work during IAP to do 4 things:

  1. To go to court, obtain eviction files, and photograph those files;
  2. To code those files, which we will explain how to do;
  3. If you have programming skills, to scrape the data from MassCourts and from the Assessing office;
  4. To partner with us in analyzing the data, if you are interested.

We hope to complete the data gathering and coding during IAP and will work closely with the students on both aspects of the work.  Ideally we would start on Monday, January 7, but the work itself can happen on a somewhat flexible schedule.

Prerequisites: None.

Contact: Justin Steil (steil@mit.edu)


11/30/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Prof. Yang Shao-Horn

Project Title: Investigation of new positive electrode chemistry

Project Description: The project entails working on electrode design and better understanding a new positive electrode chemistry that is being developed to potentially offer higher energy density than commercial Li-ion batteries. Project work involves fabricating, testing and characterizing electrodes in a lab setting.

Glovebox and related experience an asset, but not required.

Prerequisites: Glovebox and related experience an asset, but not required.

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

Contact: Graham Leverick (leverick@mit.edu)


11/30/18

Term: Spring

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

MIT Faculty Supervisor Name: Prof. John Williams

Project Title: Cryptocurrency Mining: a sustainable approach

Project Description: A major criticism of Bitcoin and other cryptocurrencies is their massive waste of energy used in performing the mining that secures the transactions. This mining involves solving a simple but statistically difficult problem. A better alternative would be to use this processing might for more sustainable uses. This project will involve researching various ways of using the might of mining computation in a way that benefits humanity, and powers this new paradigm in the internet's story.

Prerequisites: General blockchain knowledge, experience in JavaScript/Node.js desired.

Contact: Sam Raymond (sjr@mit.edu)


11/30/18

Term: Spring

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

MIT Faculty Supervisor Name: Prof. John Williams

Project Title: New Applications of Ai in Numerical Simulation: Matrix Inversion

Project Description: Deep learning and other machine learning techniques have begun making real world impacts on everyday life, from translation in real-time to facial recognition. Much of the interest in neural networks lies in the convolutional neural layers. These layers allow the network to "read" an image. Currently, researchers are looking into alternative use cases for these layers. This project will focus on using these layers on matrix inversion. Matrix inversion is a crucial component to thousands of technologies used every day. This process has been studied by mathematicians for decades and the algorithms have become extremely elegant and complex to reduce the time taken to perform these inversions.

Prerequisites: Experience in MATLAB and/or Python desired.

Contact: Sam Raymond (sjr@mit.edu)


11/30/18

Term: Spring

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

MIT Faculty Supervisor Name: Prof. John Williams

Project Title: Fast Physics: Combining AI and Numerical Simulations for faster mechanics

Project Description: Deep learning and other machine learning techniques have begun making real world impacts on everyday life, from personal assistants to driverless cars. A new application of this area of Artificial Intelligence is in predicting the physics of a system as time unfolds. This project will focus on building a framework that uses synthetic data to train a neural network engine capable of understanding the laws of physics to speed up numerical simulations.

Prerequisites: Experience in TensorFlow and/or MATLABs Neural Network Framework desired.

Contact: Sam Raymond (sjr@mit.edu)


11/30/18

Term: Spring

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

MIT Faculty Supervisor Name: Prof. John Williams

Project Title: Additive Manufacturing – a simulation approach to understanding this complex process

Project Description: Creating new structures using the advances in additive manufacturing, or 3D printing, is allowing designers and engineers to build objects that were once thought impossible. A key tool of any designer is a simulator that can predict the critical stresses present in the structure under loading so that the safety can be ascertained. This project will look into further developing a 3D simulation engine to incorporate 3D printing processes to better understand the physics that occurs in the printing process.

Prerequisites: Experience in Python and/or C++ desired.

Contact: Sam Raymond (sjr@mit.edu)


11/30/18

Term: Spring

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

MIT Faculty Supervisor Name: Prof. John Williams

Project Title: Movie SFX simulations based on a real-world physics engine

Project Description: 3D simulations of real-world physics are becoming more and more common in modern triple A titles and blockbuster films. Creating these simulation engines means solving the complex equations of physics that the systems obey. Once a simulator has been created it needs to be tested in different physical use cases so that its results can be validated and the simulator's limits pushed. This project involves using a simulation engine developed at MIT to recreate various physical problems, such as tidal waves and asteroid impacts, so that the simulator can be pushed to its numerical limits.

Prerequisites: Experience in Python and/or C++ is desired.

Contact: Sam Raymond (sjr@mit.edu)


11/29/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Carine Simon

Project Title: Mobile Health Startup Data Analysis & Modeling

Project Description: Cogito is a artificial intelligence start-up founded in 2007 out of research conducted at the Media Lab. Its Cogito Companion app enables continuous monitoring of patients' mental health conditions. A significant share of the global population is affected by mental health issues and Companion has the potential to significantly improve the diagnosis, treatment and outcomes for people with mental health issues. Companion has collected patient data that need to be analyzed in order to determine the effectiveness of the signals collected.

Prerequisites:

  • Programming experience in R or Python.
  • Proficiency in statistics and Machine Learning.
  • Interest in the start-up and healthcare space.

Relevant URL: https://www.cogitocorp.com/company/

Contact: Carine Simon (casimon@mit.edu)


11/29/18

Term: IAP

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

MIT Faculty Supervisor Name: Omer Yilmaz

Project Title: Mechanistic Control on the Mammalian Stem Cell Niche during Tumorigenesis

Project Description: Keywords: Adult stem cells, cancer, caloric restriction

Overview: Our lab is interested in the physiologic effects diverse diets exert on adult intestinal stem cells and the local cellular environment, and whether these effects contribute towards tumorigenesis. Adult stem cells drive tissue regeneration by undergoing either self-renewing divisions that generate more stem cells or a series of divisions that give rise to the various differentiated cell types characteristic of the tissue. Stem cells often require cues from their cellular environment or “niche” for their maintenance and function. It has become increasingly evident that stem cells are often the cells-of-origin for cancers that arise in tissues that are maintained by stem cells. Since stem cells drive tissue regeneration by integrating signals from their niches and most cancers are understood to arise from transformed stem cells, these findings raise the possibility that stem cell function, their niches, and cancer are all connected.

Project: The goal of the current project is to unravel the molecular mechanisms that govern the niche cells' influence on the neighboring stem cells under a dietary regimen of caloric restriction and to further assess the tumorigenic potential as a consequence of manipulating this mechanism within the mammalian intestine. This project utilizes multiple genetic mouse models and an organoid ex vivo culturing system. Tumor/histological analysis, mouse handling, immunohistochemistry, and microscopy will be involved.

No experience is required. Training will be provided in all areas. The UROP must be comfortable handling and dissecting mice. The ideal candidate must be enthusiastic about science and learning, and care about details. Preference will be given to candidates who can commit to IAP.

Please contact Amanda Hussey (ahussey@mit.edu) with your CV/resume along with a description that includes relevant courses and interests/reasons you would like to work on this project. Include “IAP UROP” in the subject line.

Relevant URL: Lab website: https://yilmaz-lab.mit.edu/

Contact: Amanda Hussey (ahussey@mit.edu)


11/28/18

Term: IAP/Spring

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)


11/28/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Eric Klopfer

Project Title: Mobile Educational games

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

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

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

The system is currently using React (js) and Firebase.  This IAP we plan to add a React Native client and, design and implement at least one new game.

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

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

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

Contact: Eric Klopfer (tea-jobs@mit.edu)


11/28/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Leslie Kaelbling

Project Title: Modular meta-learning and graph neural networks

Project Description: During IAP the student will help with experiments for a paper (probably an ICML submission) which combines ideas from modular meta-learning and graph neural networks. During the spring, the student will take a more active role doing research in one of these fields.

Relevant ideas:

  • Meta-learning aims at alleviating the huge data requirements of deep learning by learning a learning algorithm from multiple tasks, such that when it can learn a new unseen task from very little data.
  • Modular meta-learning: a way of doing meta-learning by training multiple small neural networks such that they can adapt to different tasks by being composed in different ways. See http://proceedings.mlr.press/v87/alet18a.html
  • Graph neural networks: type of neural network that runs on a graph and naturally generalizes to graphs of different sizes. It can be used to predict physical scenes such as billiard balls bouncing or charged particles interacting with one another. See https://arxiv.org/abs/1806.01261

IAP project: Neural relational inference (https://arxiv.org/abs/1802.04687) is the task of inferring relations between objects from observations about their states or movements; for example we can infer which particles attract or repel each other or relations between basketball players depending on their movements. We cast this problem as a modular meta-learning problem (where each 'scene' is a different task) and are making experiments to show how this reformulation leads to very big gains in data efficiency and capabilities of our models.

Prerequisites:

  • Algorithms (6.006 or 6.046 required)
  • Machine learning (6.036 required, 6.867 or other experience desirable)
  • Probability (6.008 or 6.041 or more advanced class desirable)
  • 2 years of Python experience
  • Be willing to get acquainted with meta-learning and the codebase before IAP (20 hours of work) since the timing is pretty tight.

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

Contact: Ferran Alet (alet@mit.edu)


11/28/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Hadley Sikes

Project Title: An Engineering Design Approach to Quantitative Redox Biology for the Study of Cancer

Project Description: Hydrogen peroxide (H2O2), a member of a class of chemical species known as reactive oxygen species (ROS), is an important molecule in biology due to its involvement in numerous important signaling pathways. At low levels, H2O2 promotes homeostasis, but at high levels, it promotes apoptosis. It has also been hypothesized that H2O2, at certain levels, promotes pathologies such as cancer and diabetes. However, quantitative data is lacking regarding the concentrations of H2O2 that contribute to these different phenotypes. In addition, transport and kinetics considerations have largely been ignored. Our goal is to design and use quantitative tools to develop a mechanistic understanding of H2O2 signaling and its contributions to disease and cell death, with a major application being rational chemotherapeutic design. We use a variety of techniques from molecular biology, microscopy, synthetic biology, and more. This specific project will include experimental validation of computational models, RNAi gene knockdown experiments, performing fluorescence microscopy experiments, and Western blotting.

Prerequisites: Desire to work in a wet lab and learn new techniques coupled with strong quantitative and analytical skills. Diligence and good note-keeping skills. Coursework in biology is helpful.

Relevant URL: https://pubs.acs.org/doi/full/10.1021/acssynbio.8b00174

Contact: Kassi Stein (kstein@mit.edu)


11/26/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Mei Hong

Project Title: Resonance assignment of multidimensional NMR spectra of amyloid proteins and membrane proteins

Project Description: A bottleneck in the application of solid-state NMR spectroscopy to structure determination of biomedically important proteins is the assignment of resonances observed in multidimensional NMR spectra to the amino acid sequence of a protein. Resonance assignment is a critical step towards elucidating proteins three-dimensional structures by NMR. We seek a student to conduct resonance assignment of 2D and 3D correlation spectra of amyloid proteins involved in Alzheimer’s disease and HIV membrane proteins.

The project involves working with graduate students to analyze many multidimensional NMR spectra, organize data files with python and Matlab scripts, and obtain assignment to enable the determination of full three-dimensional structures of the proteins. In addition to applying existing assignment protocols, the student will also have the opportunity to improve upon existing assignment techniques and develop new strategies to accelerate resonance assignment. A motivated student will also have the opportunity to learn modern magic-angle-spinning NMR techniques and conduct experiments. Work will be carried out 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. An ideal candidate should have basic knowledge of protein structures and protein biochemistry, coding experience (preferably in python or matlab), and a love of solving complex puzzles!

Relevant URL: http://meihonglab.com/

Contact: Mei Hong (meihong@mit.edu)


11/21/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Edward Crawley

Project Title: Interactive visualization for an autonomous resource allocation tool for communication satellites

Project Description: The System Architecture Lab in AeroAstro is looking for two UROPs to develop the front-end visualization for a dynamic resource management tool for communication satellites. The UROPs will be part of an exciting sponsored research project with SES, the largest satellite operator worldwide. The project aims to develop an autonomous dynamic resource allocation tool for their new fleet of flexible high-throughput satellites. 

The project is now in the state where we have a good understanding and description of the problem. We have done some initial modelling and developed some AI algorithms. However, due to the high complexity of the problem, we need help with an interactive visualization of the results. The front-end will also be used to communicate with the sponsor, so the UROPs will be key team members. There will be a clearly defined work package for each UROP.

Prerequisites:

  • Excited to work on a real and impactful project in close collaboration with industry
  • Creativity and out of the box thinking
  • Strong experience in Python
  • Experience with web-based development
  • Experience with Dash/plotly is a plus (we have started to create a first visualization with Dash)
  • Experience with CesiumJS or STK is a plus
  • Knowledge in RF communication is a plus

Since we also need help with setting up some infrastructure, we want to have one of the two UROPs focus more on the infrastructure, whereas the other one focuses on the visualization development. Please let us know about your preference in the application.

Because we want to make you integral part of the project, we are looking for longer term commitments with at least one day per week during Fall and Spring. Full-time availability during IAP is a plus. If you are interested in joining our team, contact us with your CV. We are looking forward hearing from you!

Contact: Markus Guerster (guerster@mit.edu)


11/21/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Prof. Ahmed Ghoniem

Project Title: Automation and control system for a decentralized biomass/renewable energy system

Project Description: In many parts of the developing world, agricultural and other biomass waste is simply burned in the open air, creating much toxic pollution. Thermochemical treatment is a process whereby this waste can be converted into solid fuel. This has the potential to provide renewable energy, create new income opportunities, reduce waste, and reduce pollution and greenhouse emissions.

The reactor has been set-up and operated successfully. However, the measurement of different parameters (weight, temperature, flowrate, pressure, level, etc.) is done manually at present. We need to add some automation and control to make the system more effective and operational with minimal user intervention. The UROP will contribute mainly in setting up data acquisition system, temperature feedback control, and motor controller for adjusting flowrate.

Prior experience with electronic circuit design, controllers/relay and Arduino platform is required. Multi-semester engagement would be preferred. Please send CV to sonalt@mit.edu in case of interest. Alternatively, if someone wish to participate in the laboratory experiments on biomass torrefaction at BATES laboratory (30 min drive from MIT, we will provide transportation), you are welcome to apply.

Prerequisites: Prior experience with electronic circuit design, controllers/relay and Arduino platform is required.

Relevant URL: http://tatacenter.mit.edu/portfolio/torrefaction-reactor/

Contact: Sonal Thengane (sonalt@mit.edu)


11/20/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Charles Stewart III

Project Title: Data Initiatives in Election Science

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

As a UROP working on this project you will:

  • Collect and organize election science data related to the recent general election
  • Learn and use Git and GitHub for version control
  • Present interesting research ideas and findings to the larger group
  • Learn additional data management and statistical programming skills
  • Contribute to ongoing MEDSL research projects
  • Work towards answering your own research questions related to election science
  • Participate in lab meetings

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

Relevant URL: electionlab.mit.edu

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


11/19/18

Term: Summer

UROP Department, Lab or Center: Mathematics (Course 18)

MIT Faculty Supervisor Name: Prof. Alan Edelman

Project Title: Mathematical Foundations of Big Data & Machine Learning

Project Description: Big Data describes a new era in the digital age where the volume, velocity, and variety of data created across a wide range of fields (e.g., internet search, healthcare, finance, social media, defense, ...) is increasing at a rate well beyond our ability to analyze the data. Machine Learning has emerged as a powerful tool for transforming this data into usable information. Many technologies (e.g., spreadsheets, databases, graphs, linear algebra, deep neural networks, ...) have been developed to address these challenges. The common theme amongst these technologies is the need to store and operate on data as whole collections instead of as individual data elements. This research explore the common mathematical foundation of these data collections that apply across a wide range of applications and technologies. Mathematics unify and simplify Big Data and Machine Learning. Understanding these mathematical foundations allows the user to see past the differences that lie on the surface of Big Data and Machine Learning applications and technologies and leverage their core mathematical similarities to solve the hardest Big Data and Machine Learning challenges. This projects seeks to strengthen the mathematical foundations of Big Data and Machine Learning.

Prerequisites: Matrix mathematics and/or linear algebra are helpful. Experience with Matlab, Octave, or Julia is helpful, but not a requirement.

Relevant URL: https://mitpress.mit.edu/books/mathematics-big-data

Contact: Dr. Jeremy Kepner (kepner@ll.mit.edu)


11/15/18

Term: IAP/Spring

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Cynthia Breazeal

Project Title: A robot that can recognize and react to human emotions in real-time interaction

Project Description: Learning language and literacy at a young age is important, as children’s early language ability can impact their later educational success. A variety of technological interventions, such as social robotics, were designed to help support children’s early language learning (such as vocabulary skills). Thus, our project is to develop a robot peer that can facilitate children's English word learning in a personalized way.

To engage a child in a personalized word learning activity, the robot needs to assess the child's learning state (such as learning progress and semantic acquisition process) and adapts its interaction strategies to promote their learning. In the interaction, the robot should coach the child, providing hints and explanations when detecting the child's struggling with understanding a word's meaning. Conversely, the robot should also encourage the child to practice more by purposefully behaving as a tutee and letting the child to teach the robot. In our last project, we developed a Reinforcement Learning based robot behavior policy to enable a robot to deliver a personalized teaching strategy to a child.

The current robot behavior model does not recognize and react to any child’s real-time emotions (affects) expressed through their facial expressions, but we know that the emotional intelligence is crucial for robots to interact with children. Thus, we aim to develop an affective expression model that enables a robot to detect and analyze a child’s affects in real time during interaction and then select a personalized affective expression to the child.

You will integrate a cutting-edge affect recognition tool (Affdex) into our child-robot interaction system, implement robot’s behaviors, program two social robots (Jibo and Tega), and build a data analysis tool that will help uncover the interaction dynamics between a robot and a child.

Prerequisites: This position requires you to work at least 30 hours per week for the entire IAP period. You may continue the work in the spring semester. Please indicate whether you plan to do research for credits or fundings during IAP.

Required skills:

Python, APIs, statistical analysis, Unix

Relevant URL: http://robotic.media.mit.edu/

Contact: Huili Chen (hchen25@mit.edu)


11/15/18

Term: IAP/Spring

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Cynthia Breazeal

Project Title: Develop a multimodal data synchronization and visualization platform for parent-child interaction data

Project Description: We are researchers from the Personal Robots Group at Media Lab! Really would love to have you in our group!

Context

Learning a language at a young age is very crucial for children’s later educational. However, a major problem faced by many children from low socioeconomic status (SES) families today in learning a language is a lack of resources and developmentally important stimulation in their homes and schools. This lack of relevant resources and experiences for many young low SES children leads to a detrimental effect on their language and literacy development. For example, preschool-age low-SES children raised in families had significantly smaller vocabularies than high-SES children, and these differences even magnified over time. Children from low-SES households appear to have less high-quality social, responsive and facilitative interactions with their parents, which are especially crucial for their language development.

Project Description

Thus, we are hoping to bridge this participation gap in early childhood learning. This project aims to understand the mechanisms behind parent-child language-related interaction among families with varying SES levels. We will be collecting a very rich dataset on such interaction between parent and child from multiple data modalities (e.g., vision, physiology, speech, brain activity). Since data will be collected on both a parent and child in real time for multiple families, it is very crucial to store, clean and synchronize data from multiple modalities and multiple interaction sessions seamlessly.

Your Responsibility

You will be designing and developing a multimodal data storage and synchronization tool that can automatically data from different modalities and across two stakeholders (a parent and a child) together. This tool will consist of two components: data synchronization and visualization. For the visualization part, you will design and implement a simple interface that can allow users to view and compare multimodal data on parent-child interaction easily.

Prerequisites: Required skills: Python, JavaScript, data visualization tools, data management tools

Time commitment: This position requires you to work at least 30 hours per week for the entire IAP period, and you may continue to work on it  during the Spring Semester

Relevant URL: https://www.media.mit.edu/groups/personal-robots/overview/

Contact: Huili Chen (hchen25@mit.edu)


11/15/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Ariel White

Project Title: Data Collection: Political Science Research on Protest, Incarceration, and Media

Project Description: Professor Ariel White is looking for a few UROPs to work on a few projects over the IAP/Spring semester. The student would work between 5 and 15 hours per week depending on their availability. Professor White is seeking aid on two projects: (1) a project on policing of Black Lives Matter protests, and (2) a study of how local newspapers talk about crime and race. Tasks on these projects include reading and analyzing newspaper content, coding work of various types, and other duties as assigned.

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

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

Contact: Kathryn Treder (ktreder@mit.edu)


11/15/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Marin Soljačić

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

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

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

In this project, the UROP student will develop a new scalable, low-power and parallel FPGA process architecture designed to efficiently solve NP-Hard problems. This system will mimic the optical architecture that has been recently developed by the research groups of Profs. Marin Soljačić and Dirk Englund. In addition to being a very hands-on project, with potential groundbreaking applications in computing, this work presents promising perspectives in application-oriented computing: if fully successful, our approach would enable a routing and delivering company like Amazon to reduce its carbon footprint by several orders of magnitude, or biochemists working on protein folding to decrease their simulation time from several hours today to less than a second and thus facilitate breakthrough discoveries in bioengineering and drug development.

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

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

Relevant URL: https://arxiv.org/abs/1811.02705 ; http://www.mit.edu/~soljacic/AI.html

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


11/14/18

IAP/Spring

UROP Department, Lab or Center: Center for Transportation & Logistics (CTL)

MIT Faculty Supervisor Name: Alexis Bateman

Project Title: The Sustainability Primacy Problem in Supply Chains

Project Description: Buyers and sellers who are linked together by shared supply chains do not always see and interpret ‘sustainability’ in the same way.  This research presents a new line of inquiry around this discord, which we call the Sustainability Primacy Problem.  The Sustainability Primacy Problem arises when trading partners see sustainability differently, and it is unclear to participants and/or observers whose prioritization of sustainability goals governs the interconnected supply chain. This project will analyze publicly available sustainability reports across supply chains to uncover how different companies prioritize sustainability differently.  Data will be collected using content analysis manually and if possible, automated. The student will work with two Research Scientists at the MIT Center for Transportation and Logistics, Drs. David Correll and Alexis Bateman to understand the spread of available information, code the information, and analyze it upon preliminary results.

Prerequisites: We are looking for someone who is strongly motivated and interested in the topic of study. The project is open to all relevant majors. No experience is required, but preferred skills include high reading comprehension, information coding, and statistical analysis. Hours are flexible.

Relevant URL: sustainable.mit.edu

Contact: David Correll: dcorrell@mit.edu


11/13/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Jesús del Alamo

Project Title: Artificial Synapse for Neuromorphic Computing

Project Description: For more than fifty years, dizzying progress in microelectronics and integrated circuits have revolutionized computing. Because of the recent unprecedented availability of computing power and data, a revolution in artificial intelligence has become possible. Machine learning algorithms, such as deep learning, involve large and deep neural networks, which require tremendous amounts of computation and are very power hungry. On the other hand, our brain is able to process complex information on a massively parallel scale while consuming only 1-100 fJ/synaptic event. For computing, there is much for us to learn from how the brain works.

Inspired by the brain, this project aims to study a new class of artificial synapses, called cation intercalation synapses, fabricated by the researchers at the groups of Prof. Jesús del Alamo at EECS and Prof. Bilge Yildiz at DMSE. The undergraduate researcher will contribute towards the development of electrical testing setups, both at the software and hardware level, to characterize, study and benchmark the new synaptic devices. A student interested in the intersection of fundamental solid-state device physics, electrical engineering, and computer science is particularly welcome to apply. This position is for IAP/Spring with potential for a longer-term commitment.

Prerequisites: We seek motivated students with strong interests in the interdisciplinary practice of microelectronic devices, circuits, and machine learning. Familiarity with Python or MATLAB are desired.

Contact: Wenjie Lu (wenjie@mit.edu)


11/13/18

Term: IAP/Spring

UROP Department, Lab or Center: Media Laboratory

MIT Faculty Supervisor Name: Pattie Maes

Project Title: Bio-Digital Wearables

Project Description: The MIT Media Lab’s Fluid Interfaces group designs seamless interfaces for human augmentation. Building upon research from neuroscience, biotechnology, and machine learning, the Fluid Interfaces group designs systems that help us exploit the untapped powers of human body to supplement our natural abilities to support attention, memory, emotion regulation, creativity, learning, decision making and more. The group designs wearable and immersive systems that enhance people's cognitive abilities to enable them to maximize their potential. We are seeking motivational UROP(s) who are interested in working on a novel bio-digital wearable and ubiquitous device for realtime/continuous digital sensing and monitoring of biomarkers. Our aim for the project is to develop a system that is capable of :

  • 1) Longitudinal/continuous monitoring of body biological data
  • 2) Plug and play system that can work with multiple biomarkers
  • 3) Easily adaptable bio-digital platform

You will be responsible for designing and testing the hardware arrangement. You will gain experience of working in an antidisciplinary setting: learn to integrate your work in field different from yours. This position is for Fall/IAP/Spring with potential for a longer term commitment.

Prerequisites: The project is open to students majoring in mechanical engineering, electrical engineering, computer science, and other relevant fields. The UROP must have solid experience in mechanical design and fabrication. Also experience in electronics, embedded programming or experience of working in biological science wet lab is preferable but not necessary.

Relevant URL: https://www.media.mit.edu/groups/fluid-interfaces/overview/

Contact: Pat Pataranutaporn (patpat@media.mit.edu)


11/13/18

Term: IAP

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

MIT Faculty Supervisor: Roger Levy

Project Title: Eye tracking for language processing

Project Description: We study how humans read and process language in real time using eye tracking technology. We are looking for a highly motivated student who is interested in language to join the project during IAP. As part of the UROP, you will learn about experimental techniques in psycholinguistics, and will be in charge of running a series of experiments using a state-of-the-art eyetracker.  Upon interest, there will be a possibility to continue the UROP into the Spring semester and participate in analyzing the collected data.

Prerequisites

  • - Responsible, independent, and highly attentive to detail.
  • - Preferably 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)


11/13/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Langer

Project Title: App programming for medication information

Project Description: We are currently developing a new App to help patients and clinicians choose the right medications. The App should enable users to input medication names as well as harness image text recognition from pictures of medication packages to identify medications. The App will then automatically retrieve additional information about the medication. The project will involve programming the App for iOS and Android, testing different image recognition algorithms, implement data storage and processing, as well as data mining of public databases storing information on medications. Work will be conducted in the Langer Lab in the Koch Building for the Fall 2018.

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

Prerequisites:

  • Previous experience with programming iOS and Android Apps.
  • Previous experience with image text recognition.
  • Motivated to work in a team and great communication skills.
  • At least 12 hours per week dedicated to the project work. IAP and Spring 2019.

Contact: Daniel Reker (reker@mit.edu)


11/13/18

Term: IAP/Spring

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

MIT Faculty Supervisor Name: Cynthia Breazeal

Project Title: Game Design for Collaborative Human Robot Interaction

Project Description: Personal Robots Group at MIT Media Lab is a part of the MIT Quest for Intelligence, and has been making efforts towards AI education for K-12 students. This project is about looking at how social robots can be used to foster creative thinking in elementary school children while they program AI agents. We are designing game frameworks, where the child teaches the robot how to play the games. We are looking for someone to help us build these platform strategy games on a web platform. Additionally, if interested, the researcher can be a part of evaluating the tools with children (If IAP + Spring).

Prerequisites: Experience with Javscript, preferably React/Pixi. Experience with Unity is a plus

Contact: Safinah Ali (safinah@media.mit.edu)


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: 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)


10/30/18

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

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)


10/11/18

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)


 

10/9/18

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)


10/3/18

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)


10/1/18

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)