SuperUROP 2016–2017

ADVANCED UNDERGRADUATE RESEARCH OPPORTUNITIES PROGRAM Research Guide “Engaging in research gives our undergraduates the confi- dence to push boundaries and solve problems that no one has ever solved before. The skills students gain from Super- UROP and related programs are about more than learning how to be a researcher or academic. They provide a foun- dation for whatever they end up pursuing.” — Ian A. Waitz Dean of Engineering Jerome C. Hunsaker Professor of Aeronautics and Astronautics As we launch the fifth year of the Advanced Undergraduate Research Pro- gram, it is my pleasure to welcome a new group of SuperUROP students from several departments across MIT’s School of Engineering. Since the program began in EECS in 2012, it has equipped undergraduates with the research toolkit they need to tackle real-world problems by giving them the opportu- nity to conduct innovative, publishable research.

The 152 SuperUROP students in this year’s group are engaging in a year- long research experience and participating in a course titled “Preparation for Undergraduate Research,” which covers a range of subjects, from selecting projects and research topics across the School of Engineering to entrepre- neurship and ethics in engineering. The students also focus on developing their technical communication skills— including poster presentation, writing a detailed proposal, reviewing and critiquing technical papers, and writing a paper. Throughout the year, they are also given access to facilities (e.g., MTL nanofabrication) that would otherwise be typically available only to graduate students. At the end of the academic year, the students will receive a certifi- cate in advanced undergraduate research.

I am thrilled to hear from members of the previous SuperUROP classes about the exciting new directions they are taking, benefiting from their experience in the program. Several students have gone on to publish their research in premier journals. Many are now earning advanced degrees at major research universities, making an impact in industry, or working as part of the team at cutting-edge early-stage startups — their research has set very high stan- dards. After reviewing this year’s proposals, I expect another exciting year of publication-quality research. The new SuperUROP group is eager to engage in the research and entrepreneurship opportunities that open up through this unique program.

SuperUROP is a collaborative effort involving EECS, the MIT UROP Office, and Top: Electrical the School of Engineering. Our students are supported by the Research and Engineering senior Uttara Innovation Scholars Program (RISP), a named scholars program that funds the Chakraborty stands next student doing the SuperUROP and provides some associated discretionary to the optics setup in funding for the host research group. This program would not have been pos- Quantum Photonics Lab. sible without generous support from corporate and individual sponsors, all Chakraborty has been of whom are committed to growing the SuperUROP program and enhancing working with Prof. Dirk Englund on a project the student experience at MIT. I would like to extend my sincere thanks to aimed at designing SuperUROP’s sponsors, who are listed on page 44 of this brochure. quantum dot-based single photon sources. I am very excited about the research projects in the program and I look for- ward to a productive year of collaborations among students, supervisors, and sponsors. Bottom: Computer Science senior Anita Liu works with Dr. Elizabeth Choi on her Sincerely, SuperUROP project. Liu is working with the Research Anantha P. Chandrakasan Laboratory of Electronics Vannevar Bush Professor of Electrical Engineering and Computer Science (RLE)’s Speech Commu- Department Head, MIT Electrical Engineering and Computer Science nication Group on an acoustic cue system that analyzes children’s speech with the goal of identi- fying early indications of language impairments.

1 Electrical engineering senior Sarah Hensley is working with a team of researchers in Prof. Russel Tedrake’s lab to prepare Valkyrie, a humanoid robot also known as R5, for future space missions.

MIT AeroAstro — Boeing Undergraduate Research and Innovation Scholar Oliver Jia-Richards MIT AeroAstro — Draper Laboratory Undergraduate Research and Innovation Scholars “Cisco is committed to driving innova- Bjarni Örn Kristinsosn tions in networking and information Michael Picchini technologies that transform the way we work, live, play, and learn. The network MIT AeroAstro — EECS Undergraduate Research and is undergoing the largest architectural Innovation Scholar shift in decades. We are thrilled to partic- Rachel Morgan ipate in MIT EECS’s SuperUROP program MIT AeroAstro — Lincoln Laboratory Undergraduate Research to work with Anantha Chandrakasan and and Innovation Scholars the SuperUROP students, faculty, and Joseph Figura staff to create innovations for the next Erika Hill generation of networked experiences.” Solan Thomas Israel-Megerssa William Enrique Lopez-Cordero — Susie Wee ‘90, SM ‘91, PhD ‘96 Maya Nasr Zhishen Wang VP and Chief Technology Officer of Networked Experiences, Cisco MIT AeroAstro — Lockheed Martin Undergraduate Research and Innovation Scholar Clementine Mitchell RESEARCH & INNOVATION SCHOLARS & INNOVATION RESEARCH MIT AeroAstro — Northrup Grumman Undergraduate Research and Innovation Scholar Samir Wadhwania MIT AeroAstro — UTC Pratt and Whitney Undergraduate Research and Innovation “I saw that my lab work Scholar and that of others could Timothy Nguyen MIT BE — Microbiome — Undergraduate Research and Innovation Scholars actually lead to improved Preksha Bhagchandani medical imaging and better Chaarushena Deb Alexa M Garcia care. I learned how things Summer Gu Katy Johnson actually get accomplished Navil Perez through research.” MIT CEE Undergraduate Research and Innovation Scholars Erin Reynolds —Tally Portnoi Brenda Stern SuperUROP Class of 2015-2016 MIT ChemE Undergraduate Research and Innovation Scholars Andres Felipe Badel Isaiah Borne Marjorie Buss Faben Girma Minsoo Khang Luzdary Ruelas Jessie Zhao MIT EECS — Analog Devices Undergraduate Research and Innovation Scholars Vineel Chand Adusumilli Uttara Chakraborty Jared Counts Ignacio Estay Forno Jitesh Maiyuran Rachel Yang Chengkai Zhang MIT EECS — Angle Undergraduate Research and Innovation Scholars “I love SuperUROP because Andreea Bobu it gave me a bigger project Bingfei Cao Madeleine Duran to work on. It really helped Courtney Guo Sarah Hensley me be independent, as well Ziwen Jiang Hanna Lee as challenging me with Weerachai Neeranartvong projects like the poster Kyle Swanson Jimmy Wu session and writing papers.” Rujie Yao MIT EECS — Cisco Undergraduate Research and Innovation Scholars Benjamin Y Chan —Christian Argenti Changping Chen SuperUROP Class of 2015-2016 Douglas Chen Aditya Gopalan Paul Kalebu Preksha Naik MIT EECS — Draper Laboratory Undergraduate Research and Innovation Scholars Lilly Chin Martin Krasuski Alex LaGrassa Jimmy Mawdsley Mayuri Sridhar

3 MIT EECS — Fano Undergraduate Research and Innovation Scholar William Arthur Noble MIT EECS — Finn Undergraduate Research and Innovation Scholar Dina Levy-Lambert MIT EECS — Hewlett Foundation Undergraduate Research and Innovation Scholars Mehmet Efe Akengin David Pineiro Hyunjoon Song Erjona Topalli Hugo Zul MIT EECS — Keel Foundation Undergraduate Research and Innovation Scholars Dhroova Aiylam Hyun Sub Hwang Jing Chao Lin Varun Mohan William Moses Elisa Young MIT EECS — Lal Undergraduate Research and Innovation Scholars Tiffany Ann Chen Ryan Chung Andrew Mullen Rajeev Parvathala Mark Wang “Engineering possibilities MIT EECS — Landsman Undergraduate Research and Innovation Scholars Alexander Nordin has been the cornerstone Ertem Nusret Tas of Draper capabilities MIT EECS — Lincoln Labs Undergraduate Research and Innovation Scholars throughout its more than Rohan Banerjee 80-year history supporting Landon Carter National Security and Com- Kevin Chan mercial customers. With the Michael Janner enhanced experience Su- Amir Karamlou Erika Lu perUROP provides to elec- Jordan Lucier trical engineering students Matt McEachern they appreciate more fully Rishad Rahman the value and importance Divya Shanmugam Rahul Sridhar of continuing to push the envelope of possibilities in MIT EECS — Lockheed Martin Undergraduate Research and Innovation Scholar the field and their subse- Brian Wheatman quent impact on our lives.” MIT EECS — Mason Undergraduate Research and Innovation Scholars Andrea Li — Kaigham J. Gabriel Ali Soylemezoglu MIT EECS — MITRE Undergraduate Research and Innovation Scholars SCD ‘83, President and Cordelia Avery CEO, Draper Rosemond G. Dorleans Ryan Kelly Amber Meighan Varot Premtoon Andrew Xia MIT EECS — Morais and Rosenblum Undergraduate Research and Innovation Scholars Aneesh Anand Demitri Nava MIT EECS — Quick Undergraduate Research and Innovation Scholars Mohammed Al Ai Baky

4 Suma Anand Valerie Sarge MIT EECS — Seven Bridges Genomics Undergraduate Research and Innovation Scholar Linh Nguyen MIT EECS — Slaughter Undergraduate Research and Innovation Scholars Calvin Huang Huy Dang Pham Mengjiao Yang MIT EECS — Texas Instruments Undergraduate Research and Innovation Scholars Sourav Das Allison Lemus Ayrton De Jesus Munoz Daniel D. Richman MIT EECS Undergraduate Research and Innovation Scholars William Caruso Abigail Choe Dustin Doss Emily Maria Giurleo Nathan Hunt Mohamed Hassan Kane Jamarr Kyle Lampart Hane Lee Denis Li Anita Liu Amin Manna Electrical engineering and Olivier S. Midy computer science senior Khaled Moharam Battushig Myanganbayar Ebenezer Nkwate is working on Ebenezer Nkwate a project with his advisor, Prof. Byungkyu Park Timothy Lu, to design genetic Jeanine Pearson logic gates for improving heart Gailin Pease Marcos Alberto Pertierra functioning. Shraman Ray Chaudhuri Maria Ximena Rueda-Guerrero Shinjini Saha Mehmet Tugrul Savran Alisha Saxena Yinghua (Kelly) Shen Cooper Sloan Lawrence Jialin Sun Michael Sun Andy Wang Li Wang Mike Wang Sze Nga Wong Raymond Wu MIT NSE Undergraduate Research and Innovation Scholar Logan Abel Undergraduate Research and Innovation Scholars Peniel Argaw Jonathan A Garcia-Mallen Lucas Eduardo Morales Ajay Saini Manjot Sangha Sanjana Srivastava Madeleine Waller Helen Zhou

5 Logan Abel Vineel Adusumilli MIT NSE Undergraduate Research MIT EECS — Analog Devices and Innovation Scholar Undergraduate Research and Project: Development of the Innovation Scholar Concept of Wigner Energy Project: Accelerating Embedded Advisor: Michael Short Algorithms for Low-Power Machine Learning and Computer The core of a nuclear reactor is a Vision physically hostile area: a maelstrom Advisor: Vivienne Sze of energy, heat, and movement within which the materials that compose the core must withstand fluid corrosion and degrada- The purpose of this project is to optimize and implement com- tion. Coupled with these purely chemical damages are the effects puter vision and machine learning algorithms for use on cheap of intense radiation damage from the nuclear fuel. Predicting how low-power embedded devices. This will also be useful in systems the materials that make up the nuclear reactor will act is of vital requiring multiple cameras where processing can be done at the importance. Through this research project, we will be expanding devices themselves and video data does not need to be sent to a the concept of Wigner energy, a unit of stored energy to measure centralized server. radiation damage. We will be performing both irradiation exper- iments and measurement with differential scanning calorimetry “I wanted to get hands-on research experience in a world-class (DSC) as well as computational validation using molecular dynam- laboratory.” ics (MD) simulations to quantify Wigner energy in a range of mate- rials.

“I have had the opportunity to do computational research in nuclear in the past, and I am excited to learn about the exper- imental side of the field. I enjoy exploring interconnection between theory and practice as it is a realm where we validate and potentially change our theories through the experimenta- tion, and put our understanding of our physical reality to the test.”

Dhroova Aiylam Mehmet Efe Akengin MIT EECS — Keel Foundation MIT EECS — Hewlett Foundation Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: Semidefinite Relaxations Project: Cross-modal Visual of Surface Deformation Problems Learning Advisor: Justin Solomon Advisor: Antonio Torralba

In this project, I will be working with Learning the features of different Justin Solomon to explore how non-convex optimization problems visual modalities like natural image, sketch and drawing and trans- that arise in surface modeling can be suitably relaxed into convex ferring features from one modality to another modality is an active ones. In particular, we hope to be able to apply some variation of area of research. The convolutional neural networks have shown a the technique in the paper “Global Registration of Multiple Point preliminary success in transferring the high level features to natu- Clouds Using Semidefinite Programming” by Chaudhury et al. to ral image modality. My work builds on the existing research done the problem of as-rigid-as-possible surface modeling. This would in MIT Vision Lab to create machine learning models that can learn avoid the problem of local minima, instead allowing for recovery the features of different modalities and transfer the high level fea- of the globally optimal solution. tures of one modality to another one.

“I’m a senior studying math and CS. I’m interested in the proj- “I believe that SuperUROP is a fantastic opportunity to ect since it deals with mathematical aspects of machine learn- research in a more systematic way and be acknowledge for ing, which is a subject I’ve wanted to explore. I hope to learn the research. I have been doing research in Vision Lab since some geometric/linear algebraic techniques in surface mod- Fall 2015 and I would like to continue working in this fantas- eling, and the methods used to relax provably hard prob- tic group. I hope to hone my skills in computer vision and deep lems. Constructing an appropriate relaxation that could learning and also work on a research project with more free- lead to to better practical results would be very exciting.” dom. I am excited to be advancing the computer vision field.”

6 2016– 2017 Scholars Mohammed Al Ai Baky Aneesh Anand MIT EECS — Quick Undergraduate MIT EECS — Morais and Rosenblum Research and Innovation Scholar Undergraduate Research and Project: Developing Quantum Innovation Scholar Information Processing Devices Project: Probabilistic Computing and Free Space Optics Systems Advisor: Vikash Kumar Mansinghka Advisor: Dirk R. Englund The recent increase in the volume This project implements and tests and variety of data has raised ques- an FPGA-based controller of a quantum photonic chip used in tions about the methodology used to conduct real-life data anal- Quantum Key Distribution (QKD) experiments. The controller is ysis. Statistical inference problems include detecting predictive a 4-channel serializer of the data to be quantum-encrypted and relationships between variables inferring missing values and transmitted. It runs at 1 GHz, and it allows the control of the output identifying statistically similar database entries. BayesDB is a plat- signal voltage level through a 4-channel 16-bit Digital-to-analog form for data analysis that is built on a non-parametric Bayesian Converter (DAC). meta-model that automatically infers a series of mixture mod- els from datasets. I will focus on the evaluation of BayesDB with regards to two of its chief functions: (1) its ability to detect depen- “I’m interested in developing widely used applications based on dencies between variables in datasets and (2) its ability to retrieve the quantum mechanics phenomena. I hope to use my engineer- and order database records by similarity to known or hypothetical ing skills and quantitative intuition to push forward the develop- records of interest by testing its performance on various datasets. ment of real-world applications from theoretical works in quantum mechanics.” “I’m participating in SuperUROP because I haven’t had the oppor- tunity to do in-depth research before. I wanted to pursue it seri- ously to try to get a sense of whether research is a path that I would like to continue on. I find my project exciting because I’m learning a lot not just about the research but about the field of data science as a whole which is really exciting.”

Suma Anand Peniel Argaw MIT EECS — Quick Undergraduate Undergraduate Research and Research and Innovation Scholar Innovation Scholar Project: Echolocation: Modeling, Project: Non-invasive Screening simulating, and fabricating for Diabetes biomimetic ultrasound receivers Advisor: Richard Fletcher Advisor: Aude Oliva Finding new methods to screen for This project concerns the develop- diabetes has been a growing focus in ment of a mobile sonar unit that uses ultrasound to sample the medical device research over the years. Although many new tech- environment for blind and visually impaired users. Currently the niques have been developed, most are arduous and invasive. The device enables users to distinguish object location along a hori- goal of my project is to focus on building a device that will be able zontal plane (azimuth) using binaural stereo cues; however the to optically inspect the skin and screen for diabetes without requir- device does not offer the spectral cues that provide elevation infor- ing invasive procedures. This device will attach to a mobile phone, mation. The goal of this SuperUROP is to design simulate fabricate which will analyze the skin and send the data to an application. and test an ear-like external receiver assembly that will spatially The application will then process the data and provide a diagnosis filter incoming signals to provide these cues. In addition to re-map- from the measurement. The intention of this device is to create a ping frequency to elevation the receivers would take advantage health diagnostic tool that will be accessible to a large number of of the natural filtering abilities of the pinna. The receivers will be people, even to those in rural regions. designed iteratively through a simulation and optimization pro- cess prior to fabrication. “I am interested in the development of technology to better the quality of healthcare and technology around the world. “I’ve always been interested in the intersection of neuroscience Through my past UROPs, I was able to work on various projects and engineering. My research experience in fMRI labs opened creating simple technologies that focused on different aspects my eyes to the complexity of the brain. This project not only has of healthcare and international development. I am eager to the potential to be developed into a user-ready aid but can also work on this project because it incorporates both electrical provide new insights into auditory perception. I’m excited to work engineering and computer science along with my interests.” with a wide range of people including the blind community to break new ground in neuroengineering.”

2016 – 2017 Scholars 7 Cordelia Avery Andres Badel MIT EECS — MITRE Undergraduate MIT ChemE — Undergraduate Research and Innovation Scholar Research and Innovation Scholar Project: Wikipedia as an Project: Cost-Effective Large- information source for the START Scale Energy Storage: Towards question-answering system the Development of Sulfur-Based Advisor: Boris Katz Redox Flow Batteries Advisor: Fikile Brushett The START question answering sys- tem pulls information from various sources to answer users’ natu- As we move towards a future reliant not on fossil fuels but on ral language questions. One such source is Wikipedia. Unlike a tra- renewable energy sources energy storage systems will play a per- ditional search engine, it returns a concise response that directly tinent role in the integration into the existing power grid. A poten- answers the question, as opposed to a list of links that the user tial avenue for this is the redox flow battery which allows for ease must manually sift through. My SuperUROP project focuses on of scalability and a simplicity of mechanism. We hope to develop extracting information from Wikipedia in such a way that it can be a redox flow battery using aqueous polysulfide and polyiodide as efficiently and accurately matched with user-generated questions. a potential alternative for existing technologies. This flow battery It will build on work I have done throughout this past year. will be optimized through membrane and catalyst screening and a sulfur speciation investigation. “As a computer science major minoring in linguistics, my project spans two of my main areas of interest. I have already done related “I am a senior in chemical engineering. This project is an inves- work in the same lab, and view this project as a natural extension of tigation into sulfur-based flow batteries. I have been work- my current research. The SuperUROP program is the perfect oppor- ing with the Brushett group since my freshman summer giv- tunity to not only work on this project, but also engage with and pres- ing me experience with characterizing redox active molecules ent to others in a way that goes beyond the reach of a normal UROP.” and with flow battery testing. I hope to learn about cata- lyst design and testing. This project excites me because I will gain experience in project development from start to finish.”

Rohan Banerjee Preksha Bhagchandani MIT EECS — Lincoln Labs MIT BE—Microbiome Undergraduate Undergraduate Research and Research and Innovation Scholar Innovation Scholar Project: Investigating the bacterial Project: Towards the Development epitope that induces CDM-IEL cells of a Robotic System with in the intestinal epithelia Conversational Audio-Visual Advisor: Hidde Ploegh Localization Capabilities + + Advisor: Jim Glass CD4 CD8αα intraepithelial lympho- cytes (CD4IEL) play a role in protection of the gut. Although little is

Robotic systems that can interact with humans have the poten- known about the signals required for differentiation of CD4IELs it is tial to fill an important niche in situations that are inherently well established that their development depends on the presence dangerous or tedious for humans, such as healthcare and disas- of the microbiota. My project will focus on expanding a previous ter relief. One component of the human-robot interaction prob- model by finding the epitope that allows CD4IEL induction. This will lem involves robotic participation in human spoken conversation, be accomplished by identifying growth conditions in which the where a robot would effectively respond to verbal instructions and antigen is not expressed and RNA sequences that are differentially non-verbal cues. In this project, we aim to demonstrate the feasi- expressed. These sequences will be tested with an in vitro prolifer- bility of a simple robotic system that can orient itself in the direc- ation assay. This expanded model system will allow us to answer tion of a speaking subject. In particular, we will implement audio outstanding questions in the field regarding the environment and and visual localization modules on top of existing hardware, and commensals required for CD4IEL development. conduct experiments to gauge the effectiveness of the integrated system under different environmental and subject configurations. “I am a course 20 junior and hope to pursue a career in medical research in the future. My experiences in UROP for the past 2 years “The SuperUROP program will give me the opportunity to apply passion for research in biology and experience in research com- the skills acquired from my artificial intelligence work on the UAV munication from 20.109 have prepared me for this project. I hope Team and my coursework in machine learning and signal process- to learn how to better communicate my research ideas in multi- ing to a challenging research project. I feel that my project has the ple formats and am excited to start a more independent project.” potential to advance the progress of human-computer interaction, hopefully bringing us closer to more intelligent robotic systems.”

8 2016– 2017 Scholars Andreea Bobu Isaiah Borne MIT EECS — Angle Undergraduate MIT ChemE — Undergraduate Research and Innovation Scholar Research and Innovation Scholar Project: Representations of White Project: Supercritical Water Matter Hyperintensity in Clinical Upgrading of Crude Oil Brain Images Advisor: William Green Advisor: Polina Golland The crude oil refining process is Analyzing the severity of cerebrovas- important for the production of fuel cular disease, such as ischemic stroke or leukaraiosis, is import- and petrochemical products that help build developed societies. ant in stroke prognosis and treatment. Cerebrovascular disease In the refining process the heavy streams of crude oil are subjected presents with high variability in shape and location in the brain, to catalytic hydroprocessing or coking to get the last available making it difficult to identify patterns or make predictions. Leu- fuel. A drawback of catalytic hydrogenation is that large amounts karaiosis, or non-specific vascular disease observable on medical of high pressure hydrogen are needed, but coking produces large images, has a more characteristic behavior – hyperintense on amounts of petroleum coke as a low-value byproduct. Crude oil T2-FLAIR imaging, often peri-ventricular, and roughly bilaterally upgrading with supercritical water (SCW) is a technique for con- symmetric. As such, I will explore mathematical representations verting heavy oils into lighter hydrocarbons. This project strives to to capture leukaraiosis in brain images. Such representations will create a lumped model that describes reaction rates of compound help in pathology segmentation and stroke prognosis, offering a groups in crude oil exposed to SCW. A better understanding of better understanding of cerebrovascular disease. crude oil reactivity in the presence of SCW could lead to new refin- ing methods. “I have been in Polina Golland’s group for a year and a half and I love my work here. My UROP project in this lab has been Hello, my name is Isaiah Borne and I am from Marietta, GA. My an incredible learning experience; as such, I want to take SuperUROP project is dedicated to upgrading crude oil. I have my research path to the next level by leading a new project worked in Professor Green’s lab since January of this year so I am through the SuperUROP program. This opportunity will expand familiar with a lot of the background research. I hope to learn about my knowledge in machine learning research and connect the research process and figure out what reactions are happening me with other professors from areas related to my research.” in a complex system. I am excited that I can learn something that could impact energy production.

Marjorie Buss Bingfei Cao MIT ChemE — Undergraduate MIT EECS — Angle Undergraduate Research and Innovation Scholar Research and Innovation Scholar Project: Heterologous Project: Inference on Protein-RNA biosynthesis of coenzyme M to Binding Structure enable engineering of alkane and Advisor: Bonnie A. Berger alkene metabolisms Advisor: Gregory Stephanopoulos My research project involves inves- tigating improvements that can be Coenzyme M (CoM) is a key cofactor in methanogenesis in archaea, made in the inference of RNA-protein binding specificities. Spe- as well as in alkene and epoxide catabolism in bacteria. These cifically, I will be investigating how both incorporating structural CoM-dependent metabolic pathways are of interest because they data of RNA as well as adding algorithmic improvements to exist- could be used for the bioconversion of harmful substrates to bio- ing models can improve their performance. Successful past mod- fuels and other useful chemicals. For instance, alkenes such as pro- els include various k-mer models as well as neural networks, and I pylene and vinyl chloride that pose potential health hazards are hope to investigate various methods through which the accuracy degraded via CoM-dependent pathways to central metabolites. of these models can be pushed beyond their existing limits. CoM-dependent pathways also assimilate greenhouse gases such as CO2 and methane. To enable these useful metabolic pathways “Hi! I’m Tony Cao, a 6-3 junior. Before MIT, I did a lot of biology, hav- to be implemented in typical metabolic workhorses such as E. coli, ing made it to USA Biology Olympiad’s national camp. Since col- CoM biosynthesis must first be engineered. This project aims to lege I have focused on computer science; however, my superUROP engineer CoM biosynthesis in E. coli by expressing known or puta- project gives me an amazing opportunity to experience intersec- tive CoM biosynthesis genes. tion of the two. I’m really excited to apply machine learning/infer- ence techniques to the unique datasets of biology and hopefully “I am a junior majoring in Chemical-Biological Engineering and produce some interesting results!” Biology. I worked in the Stephanopoulos Lab last year, and this year I will continue in the lab on a new but related project for SuperUROP. I am excited to engineer the biosynthesis of CoM to enable engineering of useful metabolic pathways. I am also glad to improve my laboratory and research communication skills, as I plan to pursue a PhD after MIT.”

2016 – 2017 Scholars 9 Landon Carter William Caruso MIT EECS — Lincoln Labs MIT EECS Undergraduate Research Undergraduate Research and and Innovation Scholar Innovation Scholar Project: Accessibility of Mobile Project: Computational Design for Apps Printable Hydraulic Robots Advisor: Lalana Kagal Advisor: Daniela L. Rus Handheld devices have replaced Existing 3-D-printers cannot print desktops and laptops as the primary fully-integrated actuated structures, yet 3-D-printed robots will communication and computation platform for many individuals. require this capability. To this end, the Distributed Robotics Lab With almost one billion people with disabilities in the world, ensur- has developed a 3-D printing technique that enables the print- ing that apps for these handheld devices are accessible by people ing of hydraulic elements directly as part of a superstructure. This with disabilities is important and becomes highly critical during development has allowed one-shot printing of functional robots, emergency situations, when dissemination of evacuation informa- requiring only the addition of electronic components. At this stage, tion and coordination of relief efforts are essential. Though mobile however, the software interface for generating print files has no apps are mostly covered by the same accessibility standards as validation step — this research will create a validation package to web applications, there aren’t sufficient tools for developers who ensure print parameters are met, such as overhang support, void want to build accessible mobile apps. This project aims to design detection, wall thickness, etc. After this is complete, the computa- and develop relevant libraries and toolkits to enable the develop- tional design of hydraulic robots will be investigated, posed as a ment of accessible mobile apps. machine-learning optimization problem. “I am excited to commit to a year-long research project. I am “As a 2 & 6 double major, 3-D printed robotics is an incredibly inter- also excited about my research: I have a nation for mobile apps.” esting field, allowing me to use knowledge and intuition from both majors. I hope to gain experience in 3-D printed robot design, and in particular, machine learning for robot design. Finally, I chose the SuperUROP program to aid in structuring the research, pro- viding a timeline, goals, and an audience to share my results.”

Uttara Chakraborty Benjamin Chan MIT EECS — Analog Devices MIT EECS — Cisco Undergraduate Undergraduate Research and Research and Innovation Scholar Innovation Scholar Project: Cognitive Management Project: Highly Efficient Single- and Control of Optical Photon Sources Based on Metropolitan Area Networks Nanoscale Optical Positioning and Advisor: Vincent W.S. Chan Hybrid Photonic Integration Advisor: Dirk R. Englund We seek to develop a new way of managing optical Metropolitan Area Networks (MAN), motivated Single photon sources are essential to quantum key distribution, by increasingly bursty and unstructured high-volume traffic. By quantum computation, and quantum optical communication. This using cognitive techniques, we can 1) detect, predict, and estimate SuperUROP aims to develop highly efficient fiber-integrated single these traffic loads, and 2) optimize resource scheduling and load photon sources for various quantum information processing appli- balancing across the network. This project specifically focuses on cations. Self-assembled epitaxially-grown semiconductor quan- designing algorithms to dynamically achieve high network perfor- tum dots (QDs) are among the best candidates for on-demand mance, developing theoretical models for these algorithms, and single photon sources, but incorporating them into engineered running simulations to confirm the results. photonic environments presents significant challenges. In order to efficiently extract broadband single photons emitted by the QDs, “I’m incredibly interested in how we can derive simplicity and ele- we will use “bullseye” gratings fabricated in GaAs with a single layer gance from chaotic systems, and this SuperUROP project explores of embedded InAs QDs. My goal is to functionalize optical fibers exactly that! We’re investigating optical networks that are home to with such QD-embedded bullseyes to create versatile “plug and surprisingly bursty and unstructured traffic. It will be exciting to play” single photon sources. infer (from this ‘unknown’ traffic) how best manage the network. My background is an intersection of distributed systems, neurosci- “As a senior in electrical engineering and physics, I have always ence, and CS theory.” been fascinated by the study of matter and light at the most fundamental level. Building on my prior experience in electronic device fabrication and micro-manipulation, I am excited to have the opportunity to apply the knowledge I gained in my electro- magnetics and quantum physics classes to a cutting-edge research problem in quantum engineering.” 10 2016– 2017 Scholars Kevin Chan Changping Chen MIT EECS — Lincoln Labs MIT EECS — Cisco Undergraduate Undergraduate Research and Research and Innovation Scholar Innovation Scholar Project: Software and hardware Project: Optimization and optimizations for event-based Application of the Eyeriss Object JavaScript programs Classification System Advisor: Daniel Sanchez Advisor: Vivienne Sze Multiple studies have shown that This project focuses on the optimization and application of a low asynchronous event-driven Javascript programs do not exploit power and offline image classification system developed by the the full potential of modern computers and tend to have mediocre Energy-efficient Multimedia Systems Group called Eyeriss. Eyeriss performance. In this research project we will build upon existing is a neural network accelerator that can be trained to complete literature and explore ways to optimize the execution pipeline object recognition tasks on streaming video at up to 35 frames per of event-driven Javascript client-side applications to make them second. The first task of this SuperUROP will be to improve the sys- more amenable to modern high-performance processors. The first tem’s classification throughput with PCIE optimizations between step is to set up performance simulation and analysis tools. We will Eyeriss and a NVIDIA TK1 development board. The second part of then explore both software and hardware approaches to optimize this SuperUROP aims to integrate the Eyeriss system onto a small the pipeline. Once we have fully developed the techniques, we RC car and to begin to explore the possible applications of this intend to validate their applicability in server-side applications as system in autonomous vehicles or other environments that could well. utilize fast and local image recognition. “I have a strong interest in systems and I also enjoy working “I’m participating in SuperUROP because I feel that my proj- on hard engineering problems. This project is a great fit for ect will give me experience in a cutting edge field. With vision me as it combines both and presents an exciting challenge in processing becoming a widely used technology, I’m glad my which I can apply the knowledge I’ve learned in classes and SuperUROP is giving me valuable experience in a field that may make a meaningful contribution. Along the way, I hope to learn otherwise be hard to enter as an undergrad. My experiences more about doing academic research and make some friends.” on MIT Formula SAE and lab classes have prepared me well for this position by giving me practical, hands on knowledge.”

Douglas Chen Tiffany Chen MIT EECS — Cisco Undergraduate MIT EECS — Lal Undergraduate Research and Innovation Scholar Research and Innovation Scholar Project: Fast Transactions And Project: Evaluation of Statistical Recovery With Commodity Storage and Machine Learning Approaches in Replicated Multicore Databases to Modeling Medical Time Series Advisor: Barbara H. Liskov Data Advisor: Roger Mark Databases traditionally use slow per- sistent storage like hard disks, but some recent databases primar- This project focuses specifically on the problem of incorporating ily use main memory instead. They achieve higher throughput time-series clinical care data into clinical prediction and decision and lower latency, but are more expensive and limited in terms support tools. The objective is to to develop approaches that can of dataset size. One example is Silo: it uses data structures opti- interpolate, extrapolate, and reduce the dimensionality of the time mized for concurrent in-memory access on modern multicore series data for several different types of repeatedly measured clini- machines, resulting in extremely high throughput. This project will cal data. Methods with existing software will be used to model the extend Silo to support modern persistent storage such as flash and time series data. Different approaches will be evaluated by cross non-volatile memory. The goal is to preserve Silo’s speed for work- validation and Monte Carlo simulation. We hypothesize that the ing sets that fit in memory, while still allowing good performance optimal method will differ and depend on both the objective of on larger datasets. This project is closely related to another project the analysis and the clinical variable under consideration. Hence, to improve Silo’s recovery speed through replication, and integrat- special care must be taken with sparsely measured data, or when ing the two will be a major component. the frequency of clinical tests vary significantly between patients.

“Last year I did a UROP with Professor Liskov on a project intended “I took a SuperUROP because I wanted an intense research project to make writing performant concurrent programs easier with trans- requiring continuous commitment. This project is a good match actional data structures. Most recently I worked at SpaceX, improv- for me because it builds both on the machine learning techniques ing the scalability of their in-house distributed GPU combustion I’ve learned as well as the statistical experience I’ve gained from simulator for rocket engines. I’m interested in high performance past research projects in working with clinical data. Mostly, I am and distributed systems, and I hope to deepen my understanding excited by the opportunity to make an impact at the intersection about them through this SuperUROP.” of medicine and technology.”

2016 – 2017 Scholars 11 Lilly Chin Abigail Choe MIT EECS — Draper Laboratory MIT EECS Undergraduate Research Undergraduate Research and and Innovation Scholar Innovation Scholar Project: Use of Diversity for Project: Deployable Robotic Effective Ensemble Modeling Structure Using Novel Handed- Advisor: Una-May O’Reilly Auxetic Framework Advisor: Daniela L. Rus With the rise of cloud services resources from all over the world can Auxetic materials have a lot of potential for innovative robotic now be easily compiled. In the field of machine learning and evo- applications but are surprisingly underinvestigated for possible lutionary computation this prompted the development of FCUBE applications. We have created a novel chiral auxetic pattern that a cloud machine learning framework for automatic deployment of demonstrates increased strength and stiffness under tensile load existing learning algorithms. FCUBE runs all the learners on a given than normal. We plan to use this framework into larger structures data set and returns a merged model. Such approach however – whether in metal bridges or fully-actuated robots enabling may be ineffective and time-consuming due to bias from weak greater possibilities in robotic designs. or overlapping learners. This problem will become more serious as the number of learners on FCUBE increases and hinder its per- “I am participating in the SuperUROP program because I wanted formance significantly. Therefore this project will develop a better to have a year long project that would be the culmination of all merge algorithm that will fuse the models selectively based on of my prior research experience. As an Electrical Engineering individual learner’s performance and diversity of the set of learners and Computer Science major minoring in Mechanical Engineer- to be combined. ing this project really appeals to my interdisciplinary strengths and has a lot of applications in new and innovative robotics.” “I have done two internships in the past—both of which I really enjoyed. They provided me with a dynamic but friendly environ- ment where I was challenged and grew as a result. During the semester I missed being in such an environment and decided to participate in SuperUROP so that I can continue to learn as well as contribute to a bigger project outside of the classroom.”

Ryan Chung Jared Counts MIT EECS — Lal Undergraduate MIT EECS — Analog Devices Research and Innovation Scholar Undergraduate Research and Project: Automated Sequence Innovation Scholar Annotation using Recurrent Project: Particle Shape Neural Networks Optimization For En Masse Advisor: Bonnie A.Berger Vibration Advisor: Wojciech Matusik Identifying the structure of proteins is key to understanding their underlying functions. The three-dimen- The goal of this research project is to design and manufacture sional structure depends on complex interactions between the large scale particles which as a collection can toggle between a amino acids and the cellular environment and is, therefore, a dif- locked solid state and an unlocked liquid state by vibrating them ficult task. This task can be relaxed by only considering local struc- at their resonant frequencies. Their states are highly dependent on tures within the protein, termed the protein’s secondary structure. the crystalline structures they form when packed together as well Various machine-learning approaches have been used to predict as how they act physically after packed to this state. So I will be protein secondary structure, such as SVMs, CNNs, and HMMs with implementing an algorithm which will generate an optimum pack- some success but were unable to capture long-range dependen- ing of these particles simulate these particles being vibrated after cies. In this study, we solve the problem of annotating the second- this packing and finally optimize the particle shapes in order to ary structure class of each amino acid directly from the sequence. match their desired properties. After generating candidate particle Our preliminary classification accuracy with stacked LSTMs on the shapes I will manufacture these particles using 3-D printing and TS1199/TR4590 dataset1 is over 80%. then testing to see if they match the algorithm’s results.

“My fascination with neural networks and machine learning began “The SuperUROP program gives me a chance to spend more time with my high school research and grew when I applied these tools pursuing a full fledged research projects along side my classes. I to biological systems in my UROP last summer. I‘m excited to use wish to pursue this project using knowledge I’ve learned from these skills to tackle a difficult but high-impact problem. Through Wojciech Matusik’s Computational Fabrication and Computer this project, I hope to develop as a researcher and presenter.” Graphics classes as well as from previous experiences in writing real time and offline physics simulation engines.”

12 2016– 2017 Scholars Sourav Das Chaaru Deb MIT EECS — Texas Instruments MIT BE — Microbiome — Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: Investigating Inexpensive Project: Understanding Nasal Devices to Build Conversational Polyp Cell Populations via Single- Robots Cell RNA-Seq Advisor: Jim Glass Advisor: Alex K. Shalek

One of many interesting challenges of robotics is to build a robot Nasal polyps from chronic rhinosinusitis cause complete loss of that can easily engage in spoken conversation with humans. We olfactory function. Little is known about the pathology of the con- innately use many skills to have a meaningful conversation with a dition or about endoscopic surgery prognosis the most common person or a group of people. For example, we often use different treatment option. This study will characterize the cell populations facial expressions during conversation to convey sarcasm, joy, sad- found within nasal polyps using single-cell RNA-sequencing (“RNA ness or other emotions. We can also recognize familiar voice. It is Seq”) in a Seq-Well protocol. The individual cells from the polyp useful in many cases like finding a friend in a crowd. A robot needs samples will be barcoded reverse transcribed and then amplified to have these skills to engage in human like conversation. So these to sequence the present mRNA and then characterized by gene conversational robots should be able to analyze the audio and the expression. This protocol will utilize principal component t-SNE visual data around it. To make such conversational robots available plots to quantitatively classify cell types to understand the popu- for everyone, its size and cost has to reasonable. lation of cells present in patient groups. This will give rise to better knowledge in the field regarding pathology and prognosis of nasal “I want to explore my interests through doing research.” polyps.

“I love doing research and wanted to use this opportunity to experience the rich research culture found at MIT. I’m very excited to work in such a diverse lab that brings in people of many disci- plinary backgrounds to tackle an important problem in health.”

Rosemond Dorleans Dustin Doss MIT EECS — MITRE Undergraduate MIT EECS Undergraduate Research Research and Innovation Scholar and Innovation Scholar Project: Early Enterprise Project: Improved Word Attack Detection and Target Embeddings for Analysis of Identification Clinical Texts Advisor: Howard Shrobe Advisor: Peter Szolovits

Large enterprises deploy many Clinical texts are produced in large devices, such as routers, switches, and servers, in a secure lay- volumes during the day-to-day work of medical professionals. ered architecture. The compute infrastructures are well protected The ability for intelligent programs to automatically process and behind multiple boundaries along with client level security in a understand these texts could provide opportunities for deep defense depth architecture. When cyber-attacks are identified, research or applications to aide patients and doctors alike. Within operators identify the extent of the adversary’s progression in Natural Language Processing, word embeddings are used to trans- the enterprise infrastructure to effectively combat the adversaries late plaintext words into low-dimensional vectors, allowing for without losing ground. Currently, operators spend a lot of time more complex processing. However, specific attributes of clinical identifying the attack and locating the threat before remediating text reduces the effectiveness of standard text embeddings. This it. Automated early attack detection is the key for stopping adver- project seeks to develop and evaluate improved embeddings for saries before losing the assets. For my superUROP project, I intend specified use in clinical text analysis tasks. We will initially focus to deploy an integrated and scalable algorithm for successfully on spectral embedding methods, which have been successful in detecting and locating attacks early. learning embeddings on similar datasets.

“My name is Rosemond (Ros’) Dorleans and I will be a course 6 “I’m excited by the ability for machine learning to directly and pos- senior in the Fall of 2016. My project involves creating a scalable itively affect the lives of everyday people, and this project (and the and comprehensive early attack detection algorithm to be used by work by the Clinical Decision Making Group) moves in that direc- the MITRE corporation. I have taken classes in algorithms, machine tion. Through the SuperUROP program, I hope to become more learning, as well as dabbled a bit in cybersecurity. I hope to learn confident in my research abilities and potentially find a candidate more and gain an appreciation for cybersecurity as I go further into for my graduate thesis work.” my research.”

2016 – 2017 Scholars 13 Madeleine Duran Ignacio Estay Forno MIT EECS — Angle Undergraduate MIT EECS — Analog Devices Research and Innovation Scholar Undergraduate Research and Project: Chromosome Innovation Scholar Organization and Gene Regulation Project: Single-photon-level in 3-D imaging Advisor: Caroline Uhler Advisor: Karl K. Berggren

Over the past decades great progress Knowing temporal and spatial infor- has been made in high-resolution genome sequencing; this has mation about individual photon impacts is extremely useful in led to an explosion of gene expression data from different species fields from astronomical observation to quantum information and cell types. Reconstructing gene regulatory networks from this transfer. Currently, superconducting nanowire single photon data is an important area of research and will help us understand detectors (SNSPDs) are very effective in relaying this information, the differences between different cell types and their different though there is little progress in large-scale arrays of SNSPDs as gene expression patterns. Linking the spatial and biochemical well as a framework for gathering and interpreting output signals dimensions is crucial in order to understand the mechanisms that from such a setup. The focus of this project is to find and develop a allow different cells to differentially turn on expression programs. consistent method to read and understand signals from an array of The primary goal of this project is to link whole-genome contact SNSPDs. Of focus will be the creation of a system to use the device, maps (Hi-C data) with gene expression data (RNA-seq and ChIP- optics for image projection, and development of software to inter- seq) to develop more powerful methods to infer cell-type specific pret the output from the SNSPD array. gene regulatory networks. “I’m Ignacio, a junior studying Electrical Engineering. My Super- “I’m exited to participate in the SuperUROP program and UROP project revolves around creating a system to interface with gain more experience in computational biology. This proj- nanoscale single photon detectors. My courses in electronics and ect combines my interests in math, computing and biology.” physics have helped me in my experience with the Quantum Nano- structures and Nanofabrication Group, which I’ll be conducting my research with.”

Joseph Figura Alexa Garcia MIT AeroAstro — Lincoln Laboratory MIT BE — Microbiome — Undergraduate Research and Undergraduate Research and Innovation Scholarr Innovation Scholar Project: LED Beacon for CubeSat Project: Bacteroides Virus Isolation Applications Advisor: Martin Polz Advisor: Kerri Cahoy The human gut microbiome is An LED beacon for ground station thought to play a role in several dis- geolocation for a nano satellite laser communication system will eases, including obesity and colorectal cancer. Microbiome con- be designed constructed and evaluation. Laser communication stituents display association with such diseases, but it is not known requires a beacon for ground station localization. LED beacons whether they are the cause or the effect. To determine this, we must have the potential to be cheaper and easier to implement with identify interacting pairs of bacteria and virus within the gut. In this existing satellites than existing beacons. A model of the beacon project, I investigate one set of such interactions: E. coli bacteria system will be developed and used to predict array size. A modular and phage viruses. Using a novel method, I isolate phage strains array of LEDs will be built to demonstrate this method. The array from sewage and test for infection of 16 individual E. coli strains, will use parabolic mirrors to focus a beam of light for detection by isolated from fecal donors and cultured in novel intestine-like cul- a satellite mounted camera. The performance of the system will be ture media. The outcome is a catalogue of gut E. coli:phage inter- assessed by observation by a quadcopter and satellite data and by action pairs, which may be further used in studies of the human power and thermal metrics. microbiome and virus-based therapies for associated diseases.

“In my senior year I would like to put substantial effort into a proj- With a strong background in biological engineering and virology ect I can be proud of. My SuperUROP will give me experience with research, I was interested in applying it to my passion for environ- space communications system a field that is one of my top choices mental problems. In this SuperUROP, I hope to expand my research for future work.” skill set and learn about the human microbiome and its many exciting implications and applications.

14 2016– 2017 Scholars Jonathan Garcia-Mallen Faben Girma Undergraduate Research and MIT ChemE — Undergraduate Innovation Scholar Research and Innovation Scholar Project: Localization and Project: Encapsulation of Insulin in Navigation in Mapped Waters self-assembling peptide hydrogels Advisor: John Leonard as Drug Delivery Vehicles Advisor: Daniel Anderson Crews of researchers might stay at sea for extended periods deploying Diabetes mellitus is a global epi- and running marine sensing systems. MIT Sea Grant’s 16-foot Wave demic affecting over 380 million individuals worldwide. Despite Amplitude Modulation Vessel will deploy them autonomously. It the improvements in diabetes therapy over the past two decades, depends entirely on GPS to localize itself and known obstacles. The the current therapy for both Type 1 and Type 2 diabetes relies on nearby Charles River Basin is used for recreation. Bridges along the chronic insulin use. Moreover, none of the currently available insu- river block GPS signals. Localization despite GPS failure is neces- lin treatments are glucose-responsive and capable of mimicking sary for safe operation. Mapping methods using LiDAR and cam- the dynamic functionality of the pancreas. The overall objective of eras, sensors available to our boat, are well studied. We will build this project is to investigate the in vivo applications of “smart” insu- a map using a particle filter fed by both LiDAR data and odometry lin conjugates with glucose-mediated potency and bioavailability. calculated from vision data. “I am a senior studying Chemical- Biological Engineering. I have “As member of the first-place 2014 RobotX Maritime Challenge been with my project for the the past year and a half. I chose to team and o f the MIT LAMSS group, I became intimately familiar pursue a SuperUROP because I knew that that the program would with our 16’ robot catamaran and its subsystems, particularly the provide me with opportunities to improve my skill not only as a lidar. I’m excited to finally contribute to a robot that will contrib- researcher, but also as a writer and a presenter.” ute to humanity by autonomously deploying itself and gathering oceanographic data! More than anything, I hope to learn what it means to make meaningful research.”

Emily Giurleo Aditya Gopalan MIT EECS Undergraduate Research MIT EECS — Cisco Undergraduate and Innovation Scholar Research and Innovation Scholar Project: App Inventor Project: Providing Optimal Development Information with the Advisor: Harold Abelson Informational Braess’ Paradox Advisor: Asuman E. Ozdaglar App Inventor is a website that allows users to make their own Android Driving in traffic-filled roads can be a apps using a block-based coding language. While App Inventor hassle, and apps such as Google’s Waze have stepped in to allow has almost 3 million users it contains few accessibility features. In us to dynamically re-plan our driving routes as we go to avoid particular there is no way for a user to navigate the block work- traffic and other slowdowns. Using game theory to model drivers space on the App Inventor site without using their mouse; this and graph theory to model routes, previous work has shown that poses a significant problem for users who use screen readers or there exist cases in which providing information to certain drivers who cannot operate a mouse. I will design and implement a set of decreases net traffic time, but in all other cases there is some infor- keyboard shortcuts that allow users to operate the App Inventor mation that can be given that increases net traffic time. Unfortu- website in a way that is intuitive and customizable and evaluate nately the former cases are extremely narrow and do not provide my solution by conducting user tests. an accurate model of the real world. In this work I will examine the latter cases and classify the optimal information to provide drivers “I’m participating in the SuperUROP program because I want the to optimize net traffic time among all drivers. experience of organizing and participating in a more long-term project. In my experience I’ve learned much more about software “I strive at the forefront of technology, and SuperUROP allows me engineering by undertaking projects or working on an existing to do that by designing a project with Professor Ozdaglar, a leader code base and I want to continue to gain experiences like these in in the field of optimal control, both on the academic and indus- my last year of MIT.” trial sides. I’m excited to get to apply the knowledge I’ve learned in many of my classes and UROPS as well as learning how the indus- try evaluates research and adapts it to improve our everyday lives.”

2016 – 2017 Scholars 15 Tianxia Gu Courtney Guo MIT BE—Microbiome Undergraduate MIT EECS — Angle Undergraduate Research and Innovation Scholar Research and Innovation Scholar Project: The gut microbiome: Project: Image Segmentation for Exploring microbial functions 3-D Heart Models based on metagenomic and Advisor: Polina Golland metatranscriptomic sequencing data In this project, I will develop image Advisor: Ramnik Xavier segmentation methods to delineate the heart in 3-D cardiac MRI images of patients with complex con- Various diseases are associated with an imbalance of our gut mi- genital heart disease. Image segmentation involves labeling each crobial communities. State-of-the-art sequencing approaches al- voxel with the region of the heart that it lies in. Segmenting car- low us to sequence the entire genomic content of microbial sam- diac images is important for creating patient-specific 3-D models ples as well as their gene transcripts, resulting in metagenomic of the heart, which can be displayed virtually or 3-D-printed to and metatranscriptomic data. Sequencing microbial communities help clinicians plan surgery for congenital heart disease. Currently, results in complex pools of sequences that must be computation- patient-specific 3-D heart models are underused because it takes ally analyzed to characterize which microbes are present and to around 4-8 hours to manually segment cardiac MRI images, since investigate what these microbes are doing based on the genes each contains approximately 1503 voxels. The dataset I will be they encode. In this project, we will use advanced computational working with is from Boston Children’s Hospital, which contains approaches using sequencing datasets from large human cohorts the 3-D MRI images and corresponding manual segmentations. focused on health and inflammatory bowel disease. These analyses will provide new insight into complex host-microbial interactions. “Through this SuperUROP, I want to gain more experience in medical image analysis research, as well as make a pos- “I am interested in applying data science to other disci- itive contribution to the group. I’ve taken machine learn- plines, and this microbiome project allows me to analyze ing courses and I want to expand on that knowledge with biological data that have direct translational applications.” real world applications. I hope to publish a paper by the end of the SuperUROP, if I have meaningful results to display.”

Sarah Hensley Erika Hill MIT EECS — Angle Undergraduate MIT AeroAstro — Lincoln Laboratory Research and Innovation Scholar Undergraduate Research and Project: Balance and Force Control Innovation Scholar for NASA’s Humanoid: Valkyrie Project: Cyclers as a Component of Advisor: Russell L. Tedrake Mars Campaign Planning Advisor: Oli de Weck This project evaluates the force and torque control capabilities of Valky- New and more accurate renditions of rie, NASA’s humanoid robot and entry in the DARPA Robotics the original Aldrin Cycler trajectory have been created (including Challenge. Valkyrie has series elastic actuators. The elasticity of the ballistic and low-thrust versions), but they have not been consid- springs in the actuators produces nonlinear behaviors when many ered in the context of a full Mars mission. In this research, these series elastic actuators are linked together to form neighboring cycler trajectories will be integrated into various possible Mars mis- joints. Currently, decentralized control is used to control the actu- sion architectures, by incorporating a variety of different propul- ators; each actuator individually receives input commands that sion systems, hyperbolic rendezvous maneuvers, and trajectories do not account for the position or input commands of the others. to put the cycler in orbit. For each mission architecture, total ΔV, Centralized control would allow each actuator to use information time of flight, launch mass, risk, cost, and launch windows will be from the other actuators to adjust the input commands. Thus, a either calculated or estimated. Using these quantities, the Pareto model that accounts for having many connected actuators would frontier of these architectures will be calculated and recommen- improve control of the robot, allowing for more dynamic and pre- dations on which cycler architectures are preferable will be made. cise motions. “I’m excited to do SuperUROP because I get to dive into an area that’s “The SuperUROP program gives me a chance to apply the material really interesting to me. I’m researching cyclers (objects with orbital of my favorite classes while also experiencing “real world research” trajectories designed to encounter two or more celestial bodies at — a long-term open-ended project that I direct. I did research at regular intervals) as part of a long-term strategy to bring humans the Jet Propulsion Lab and saw the DARPA Robotics Challenge last to Mars. My project has a heavy astrodynamics focus, which is great summer, but I never thought I’d get a chance to work on NASA’s because I want to do work related to mission design and navigation.” entry Valkyrie! I get to work on a dream project while also learning about research in robotics!”

16 2016– 2017 Scholars Calvin Huang Nathan Hunt MIT EECS — Slaughter MIT EECS Undergraduate Research Undergraduate Research and and Innovation Scholar Innovation Scholar Project: Deep Recurrent Models Project: Improving the for Prediction of ICU Mortality and performance of the dReal Sepsis Onset nonlinear solver by exploring Advisor: Peter Szolovits novel branching strategies Advisor: Armando Solar-Lezama Sepsis is life-threatening organ dys- function caused by a dysregulated host response to infection. The I will try to improve the dReal solver [1] for nonlinear theories over outcomes of septic patients are improved when it is identified and the reals. dReal can be used, for instance, to determine constraints treated early. I will identify sepsis and septic shock onset for the on robot movements, whether or not a task is feasible for a certain patients in the MIMIC-III clinical database according to the new robotic configuration, and what certain robot dimensions are suit- sepsis criteria. I will train a long short-term memory (LSTM) neural able for a particular task.My responsibility in this project will be to network to predict mortality or the onset of sepsis several hours studying and developing heuristics for the branching used in the in advance in a real-time forward-facing setting. I will compare my ICP solver, perhaps borrowing from existing strategies used in SAT LSTM’s predictive ability with simpler models and past work on solvers, with hopes of improving the speed and scalability of dReal. sepsis and mortality prediction. Such a model could eventually be I will be experimenting with branching heuristics adapted from used to inform ICU treatment decisions. strategies used in SAT solvers, as well as Monte Carlo Tree Search. “I’m studying computer science and molecular biology at MIT with a “I’ve studied mathematics since elementary school, and I minor in statistics and data science. It’s very important to me to make started studying computer science in early high school. I an impact with my work which is one of the reasons that I choose hope to build on that knowledge with this project; I think it’s biology as my application field. I’m also interested in AI techniques. very interesting to learn about the different techniques peo- With this project I hope to learn how to take the algorithms and skills ple have used with SAT solvers and other programs, and I’ve developed here beyond the classroom and help heal people.” how to adapt those to be used in an alternative setting.”

Hyun Sub Hwang Solan Israel-Megerssa MIT EECS — Keel Foundation MIT AeroAstro — Lincoln Laboratory Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: A Semi-automated Project: Robustness of the optical- Annotation Tool using blocking filter on the REXIS Segmentation and Multi-modal instrument under launch and Data flight conditions Advisor: John Fisher Advisor: Rebecca Masterson

Segmentation, which divides a scene into subparts while preserv- The REgolith X-ray Imaging Spectrometer (REXIS) is the student ing their local structures, provides the way to understand a scene collaboration instrument aboard NASA’s OSIRIS-REx asteroid sam- image more naturally and efficiently. One prominent example of ple return mission. OSIRIS-Rex is a NASA New Frontiers mission that segmentation is superpixel segmentation which has wide applica- will travel to the near-Earth asteroid Bennu and return a sample of tions in image and video processing. For general scene represen- the asteroid’s regolith. REXIS uses the sun as a source of x-rays to tation, different scene components can be captured from multi- image the asteroid but is sensitive to the visible spectrum of solar modal data. These multi-model data give us various information, radiation. To reduce noise, the instrument’s receivers have been including geometry and appearance of a scene. Our super urop coated with a thin aluminum optical-blocking filter (OBF). This project will develop a semi-automated annotation tool that labels arrangement hasn’t been flown before so we would like to mature scene objects when scene images, sensor data and partial anno- the OBF to TRL 6 before the instrument is deployed. My work will tations are given. The annotation tool will annotate unlabeled be to develop a plan to test a spare set of receivers for light leak superpixels in a scene from a generative model on segmentation before and after exposure to flight environments. inferred from multi-modal data. “I’m a rising junior in the AeroAstro department who is interested “I am interested in building mathematical model that explains in all things space. I’ve done thin-film analysis in the lab and have complex structure of data. I believe our project, which requires a lot of experience with scientific coding. I hope to learn some understanding of mathematical model and efficient data process- of what it means to engineer a space system. I’m definitely most ing, is the best fit for me to learn a lot. I hope to learn a lot about excited (and a little anxious) that my work will directly impact a object annotation through various probabilistic models.” piece of hardware going to space. Not many college kids can say that!”

2016 – 2017 Scholars 17 Michael Janner Oliver Jia-Richards MIT EECS — Lincoln Labs MIT AeroAstro — Boeing Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: Developing a Reward Project: A Feasibility Study of a Metric in Reinforcement Learning New Unsteady Flow Measurement through Text and Image Subgoals Technique for the Characterisation Advisor: Regina A. Barzilay of Cavitation Dynamics in Rocket Engine Turbopump Inducers Reinforcement learning provides a neurally inspired perspective of Advisor: Zolti Spakovszky how an agent learns to interact with its environment. This notion of interaction is formalized by considering policies that map states to Cavitation in a rocket engine turbopump inducer can excite lon- actions, which may or may not lead to a reward. Despite successes gitudinal vibrations of a rocket structure which potentially leads in limited domains, learning from such rewards has proven chal- to mechanical failure. To properly assess these instabilities char- lenging when the environmental feedback signal is particularly acterization of the inducer dynamics is critical. To characterize an sparse. To that effect, we will explore a means of augmenting the inducer, measurement of the mass flow and pressure fluctuations environmental reward signal with a reward function learned by the is required. Previous methods for measuring mass flow fluctuations agent itself. We will train an agent to use text directions, associated rely on a spatially averaged mass flow measurement far upstream with a representative image of the task, to aid in subgoal comple- of the inducer. This causes loss of spatial distribution information tion. The advantage to this approach is that it will be possible to and weakens the fluctuation signal. This project proposes the learn tasks for which the environment offers no explicit reward. use of fiber-film probes to take local velocity measurements near the inducer face to regain spatial information and improve the “I began doing machine learning work in Josh Tenenbaum’s Com- strength of the signal. putational Cognitive Science group. After getting some experi- ence with vision projects, I became interested in exploring another “I am a rising junior in the Aero/Astro program. I am partici- domain: language. This year I’m excited to learn more about pating in the SuperUROP program because I am interested in and bring together ideas from the natural language process- using my academic knowledge from classwork for an in depth ing, computer vision, and reinforcement learning communities.” research project. I hope to use this project to learn about a sub- ject area I am interested in pursing a career in (propulsion sys- tems) as well as gain experience carrying out a research project.”

Ziwen Jiang Katy Johnson MIT EECS — Angle Undergraduate MIT BE—Microbiome Undergraduate Research and Innovation Scholar Research and Innovation Scholar Project: High-throughput Project: Database for bacterial set Microfluidic Concentration and enrichment analysis Separation for Bacterial Detection Advisor: Eric J. Alm in Blood Advisor: Jongyoon Han Current research of human microbial communities focuses on identifying a We will develop a high-throughput microfluidic device that can single bacteria that can cause differences; however in reality these simultaneously concentrate and separate bacterial cells from differences could be caused by sets of bacteria. I propose the cura- blood in a continuous, label-free, and portable manner. For this, tion of a comprehensive database that emphasizes the ability of we will integrate ion selective membranes (ISMs) into microflu- bacteria to be searched for in sets to allow for new types of anal- idic devices as convection-preventing but current-permeating yses to be performed including enrichment analyses. Enabling salt bridges. Since most pathogens possess negative charge and analyses that utilize sets could provide a new way of looking at electrophoretic mobility, ISMs physically divide individual fluid problems in the field and eventually lead to a heightened under- streams containing pathogens at separation and electrode chan- standing of microbial interactions in humans. nels, but electrically connect each other so that an electric field can be applied to separate cells in blood, based on difference in their “I am a course 6-3 senior who is very interested in applications electrophoretic mobility and/or size. to biology that could help improve understanding of health and wellness! I will be spending the semester working on a project that “I have always been interested in biomaterials and electrical engi- combines my computer science skills with microbiome research. I neering through my previous UROP projects. It is great to partic- am looking forward to learning more about how I can use my com- ipate in a project combining both subjects. I hope to learn more puter science skills to make an impact in another field.” about microbiology and the role of electrical engineering in bio- engineering. At the same time, in this project, the interaction between electronics and bio cells in vivo really excites me since I am interested in implantation, too.”

18 2016– 2017 Scholars Paul Kalebu Mohamed Kane MIT EECS — Cisco Undergraduate MIT EECS Undergraduate Research Research and Innovation Scholar and Innovation Scholar Project: 3-D Tracking via Body Project: Learning to generate Reflections image from text Advisor: Dina Katabi Advisor: Torralba, Antonio

In recent years, multiple advanc- Recent progresses in the area of deep es have improved accuracy and learning have brought us important robustness in motion tracking and building blocks on which more sophisticated computer vision localization systems. RF localization systems, like using WiFi, have tasks can be solved. The goal of this project is to strengthen com- reached sub-meter accuracy and demonstrated the ability to puters’ ability to reason about images and objects by working on a deal with occlusions. However, these systems require the user to framework to generate image from text. The work will build on top carry a wireless device. In contrast, depth-imaging systems like of recent work on learning alignment across modalities where the Kinect revolutionize human-computer interaction by tracking 3-D same object is represented by the same embedding be it in a clip- motion without user instrumentation, but require a user to stay art, drawing or picture. With deconvolution networks, we can now within the device’s line-of-sight without occlusions. We envision generate an image from a general feature description obtained an RF system that can perform 3-D motion tracking without user using a convolutional neural networks. The present work will go a instrumentation to improve depth-imaging systems like Kinect step further and generate embedding from texts which will then to expand their reach beyond direct line-of-sight and enable be used to generate an image. through-wall human-computer interaction.

“Through two UROPs (Media Lab and LEES) and two intern- “Over the last two years, I have been fascinated by the field of ships (Intel and Apple), I have gained useful experience in cir- Artificial Intelligence for its mixing of mathematical intuition and cuit design. Additionally, past classes like 6.003 and 6.115 practical applications. After taking classes in statistical inference have prepared me well for the project. I hope to improve my and machine learning during my sophomore year and doing expertise with signal processing through the research, and I research on machine learning in healthcare in my junior year, I am most excited to work with Professor Katabi in making prac- want to explore how to make computers have visual intelligence.” tical advancements in applications of wireless technology.”

Amir Karamlou Ryan Kelly MIT EECS — Lincoln Labs MIT EECS — MITRE Undergraduate Undergraduate Research and Research and Innovation Scholar Innovation Scholar Project: Text Based Search on a Project: Enhanced Readout of Spin Video Database Qubits Advisor: Daniela L. Rus Advisor: Dirk R. Englund With recent advancements in mobile Over the past decade, the nitrogen technology, our day to day lives are vacancy (NV) center in diamond has demonstrated a great poten- being recorded in ways never thought possible before. One of tial for solid state quantum information processing. However, one those ways is through the vast amount of video due to the high of the biggest challenges in using NV as a qubit is the readout of its quality cameras on cell phones. This project aims to tackle the quantum state. Typically, this is done through measuring the flu- challenge of navigating a massive library of content with a textual orescence emission rate of the NV under laser drive, which is cor- based search. By using a k-segment mean coresets algorithm, we related to its electronic spin state. Throughout this project we are can efficiently summarize this large data set and use object detec- planning to enhance the emission rate and the farfield collection tion on the key frames in order to map sections of this library to efficiency of NV center’s fluorescence using local photonic nano- a textual representation which will allow for easy searching. This structures in order to increase the readout fidelity of the NV spin SuperUROP aims to provide a web interface allowing users to at room temperature. This will allow us to perform ultra-fast read upload content and search through their video libraries with text out of the NV center, taking us one step closer to realizing scalable based queries. solid-state quantum computation. “I am participating in the SuperUROP program because it will give “Ever since the beginning of my MIT experience, I have been UROP- me the opportunity to specialize in a field I am interested in. I am ing in the Quantum Photonics Lab, conducting research on nitro- very excited to work on a new project with the Lab I have been gen vacancy centers in diamond. I enjoyed my research experience apart of since Freshman summer and look forward to learning a lot, and that was the main reason I chose to participate in the more about computer vision and machine learning.” SuperUROP program. I will be working on the enhanced readout of spin qubits during the program, in the hope of having an impact on quantum computing.”

2016 – 2017 Scholars 19 Minsoo Khang Martin Krasuski MIT ChemE — Undergraduate MIT EECS — Draper Laboratory Research and Innovation Scholar Undergraduate Research and Project: Oral Drug Delivery System Innovation Scholar for Gastrointestinal Tract using Project: Optimizing Memory Microneedles System Performance for Graph Advisor: Robert Langer Analytics Advisor: Daniel Sanchez The goal of this project is to develop an oral drug delivery device for biologic drugs (specifically insulin) Graph analytics has gained prominence in the era of big data where that will be retained in the gastrointestinal (GI) tract. The project many applications work on unstructured data. Efficient cache uti- will focus on designing polymeric hollow microneedles that can lization is critical to the performance of graph algorithms. Unlike deliver the drug for a long time, control drug release rates and typical algorithms graph algorithms are characterized by random control time of degradation. Although an oral delivery system is memory access patterns due to their inherent unstructured form preferred by patients, the GI tract has a high pH variability and and sparsity. Random accesses patterns cause poor on-chip cache has a protease and bacteria-rich environment that makes biologic utilization and long latency accesses to DRAM. We will study hard- therapeutic delivery challenging. The needles will be housed in a ware and software mechanisms to achieve better cache utilization self-righting device that has already been developed (this sum- and graph algorithm performance. mer). The self-righting device ensures that the needle will only be actuated in the stomach (and not while traveling down the GI “I am participating in SuperUROP because I want to gain high level tract) with the right orientation. research experience in my major. I took 6.172 (Performance Engi- neering of Software Systems) last year and I enjoyed finding and “I am a senior in Course 10B and have always been interested in fixing performance bottlenecks. I’m interested in computer archi- biotech and global health. In the past, I did research on nano lipid tecture and I enjoy parallel computing problems. I’m excited to particles for mRNA delivery. I plan to go to graduate school in apply my knowledge and interests to my project.” the future, so I hope that this superUROP will prepare me well for thinking independently about an open-ended research problem.”

Bjarni Örn Kristinsson Alex LaGrassa MIT AeroAstro — Draper Laboratory MIT EECS — Draper Laboratory Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: Simulating Stall Flutter Project: Teaching Robots To and Nonlinear Divergence of a Understand Natural Language Two-Dimensional Flat Plate Wing Tasks with Lattice Boltzmann Method Advisor: Leslie P. Kaelbling Advisor: Qiqi Wang Programming robots to perform everyday tasks requires interact- As part of the resurgence of Lattice Boltzmann Method (LBM) ing with humans and their rich language structures for convey- then we want to explore if we can simulate simulate complex ing information. Robots need to operate in environments which aerodynamic phenomena such as stall flutter, vortex shedding require a lot of noisy sensor input to build a world model from or nonlinear divergence. The core code is built on top of Palabos which the robot needs to draw conclusions. One important con- Python LBM standardized code, Professor Wang’s Pascal library will clusion in human-robot interaction is determining the object a be used to translate the code into a highly parallel C code. Part of human is referring to. Evaluating lambda expressions with func- our benchmark data was collected by Prof. Dugundji back in 1972, tions that define an object lets the robot determine the probability published two years later, while the other dataset will be collected that it has found the object referred to. We need to find a way to over the Spring semester once Prof. Dugundij’s original wind tun- translate natural language into lambda expressions so the robot nel has been revamped. can include expression evaluation in its plan, including making observations that increase certainty of the world. “Without becoming overly poetic. I have always been fascinated by why some things look and behave like they do, as I learned “My project for SuperUROP integrates a lot of small questions I more science and math then the questions changed; What is it in have spent last year answering. For instance, how would a robot the flow profile that brings those capabilities and how could it be determine which object is heaviest? How does a robot create a tweaked to get a better performance and efficiency. My paint and model for what color an object is? I hope to get more mathemati- brush of choice is the interaction of coding, math and physics.” cal background to find out interesting ways of thinking about we structure language, think about objects, make plans, and how to apply that to robotics.”

20 2016– 2017 Scholars Jamarr Lampart Hane Lee MIT EECS Undergraduate Research MIT EECS Undergraduate Research and Innovation Scholar and Innovation Scholar Project: MIT Academic Social Project: Guiding Drug Titration Network During Procedural Sedation Advisor: David R. Karger Advisor: George C. Verghese

My research involves creating an aca- Procedural sedation uses drugs such demic social network to foster stu- as propofol to relieve pain and anx- dent collaboration in an academic setting outside of typical classes iety associated with medical procedures performed outside the study groups etc. This tool will be built by leveraging the existing operating room. There is currently no objective measure of seda- tools (i.e. developing more webpages and services on top of the tion level to guide the titration of medications leading to the risk current MIT Picker website) developed for easing the academic of under- or over-sedation. This research will use pharmacokinetic process here at MIT and by taking into account the pitfalls of social models to estimate the time course of the sedation agent in the networks in general as greatly discussed in the referenced papers body to provide more objective markers of sedation from a data- below. base containing information from procedural sedations conducted at two collaborating hospitals. We will also develop a tool to guide “Taking 6.170 this semester has been a great aid in my ability to the physician in real-time that displays the estimated sedation work on this research which focuses on the design and implemen- state and recommends how much additional sedation agent to tation of a social network using web technologies. I hope to learn administer and when based on the anticipated remaining duration how to best tailor my idea to best accompany as many MIT students of the procedure. as possible. I am excited by the potential of greatly reducing the stress of MIT students in navigating their academic lives while here.” “Signals and systems is my favorite field in electrical engineering. As for the human body and medication I have always considered them a mystery. I am fascinated to explore the possibilities of mod- eling the human body as a system we can control and predict.”

Hanna Lee Allison Lemus MIT EECS — Angle Undergraduate MIT EECS — Texas Instruments Research and Innovation Scholar Undergraduate Research and Project: Automated Design of Innovation Scholar Printable Interactive Robots Project: Reliability of High-Voltage Advisor: Wojciech Matusik GaN Advisor: Jesus A. del Alamo This project focuses on optimiz- ing and automating the design of GaN is a new material that shows 3D-printable robots. The first phase involves creating an applica- much higher switching speed at high voltage than Si. For this rea- tion that optimizes designs based on high level specifications of son GaN is being developed for switching regulators for AC/DC desired behavior provided by the user. Training sets consisting of converters such as wall-plug adaptors and for many other power RFID sensor data and observed human-robot interaction inform management applications from electric vehicles to smart grids. the application’s algorithms and improve its optimization strategy. Compared to Si GaN offers the potential of higher efficiency and I will explore paper 3D printing and fabricate simple prototype smaller size. However the reliability physics of GaN is different robots to validate and train the models in the application. Time in many ways from that of Si. This project aims to understand an permitting the second phase of the project will be developing an aspect of reliability physics known as dielectric reliability. The focus algorithm to simultaneously optimize the structure material com- in particular will be to examine time-dependent dielectric break- position and motion of a printable robot given high level specifi- down (TDDB) in GaN. cations. “I began this project last fall and it was my first exposure to device “I’m participating in the SuperUROP program to explore research as physics. It’s fascinating to connect a failure in a device to the inter- a career path expand my knowledge of robotics machine learning nal changes it’s gone through! Data that at first seemed random and UX and gain experience building a complex software product suddenly becomes expected and with each connection you learn from scratch. The project is interesting to me because it will enable more about how GaN behaves. I hope to discover more of the people to design and fabricate their own printable robots and the nuances in these devices and am excited to find what is physically robots will be able to use RFID technology to interact with people happening to cause them.” and the environment.”

2016 – 2017 Scholars 21 Dina Levy-Lambert Andrea Li MIT EECS — Finn Undergraduate MIT EECS — Mason Undergraduate Research and Innovation Scholar Research and Innovation Scholar Project: Identifying Characteristic Project: False arrhythmia alarm Care Patterns for Patients in the reduction in the intensive care unit ICU Advisor: Roger Mark Advisor: John V. Guttag False alarms constitute more than Patients in the critical care setting are 80% of alarms triggered in the inten- closely monitored and constantly intervened upon. While some sive care unit. This has severe implications for disruption of patient are deemed higher risks than others using metrics such as SAPS care and desensitization from clinical staff to true alarms. A method II and other physiological scores patients of all subtypes experi- to reduce this high false alarm rate would therefore greatly bene- ence adverse events. We are interested in characterizing common fit patients as well as nurses in the ability to provide care. In this “patterns of care” in the ICU and how these patterns of care may SuperUROP project we build upon previous work to build a robust differ across patient subtypes. We will attempt to better under- false arrhythmia alarm reduction system. We make use of signal stand patient ICU data by creating individual visualizations of their processing and machine learning techniques to determine if chan- stays determine subtypes based on physiological states and use nels exhibit evidence for cardiac arrhythmias. We hope to build an machine learning techniques to find patterns of care using data algorithm which performs with high sensitivity and specificity in from the MIMIC III database. We hope to learn which patterns of a retrospective and real-time setting. Such an algorithm could be care may be associated with adverse events in order to prevent translated for use in the ICU to promote overall patient care. those. “I am a junior studying computer science at MIT and I find the “I am a 6-7 and am interested in the applications of computer application of computer science towards solving medical prob- science to medicine. I started conducting research in Profes- lems to be fascinating. I am very excited for my project which uses sor Guttag’s group fall of 2014 applying machine learning to signal processing and machine learning to identify false alarms in predict medical outcomes. I will continue work on a screen- cardiac arrhythmia detection in the ICU. I hope to learn signal pro- ing tool for speech and language impairments in children. I cessing techniques and machine learning principles in the various hope to learn more about machine learning and am excited ways to help improve medicine.” to work on something that potentially will have a big impact.”

Denis Li Jing Lin MIT EECS Undergraduate Research MIT EECS — Keel Foundation and Innovation Scholar Undergraduate Research and Project: Development of an Innovation Scholar automatic speech analysis system Project: Understanding and based on human speech cognition learning visual numeracy with models attentional neural networks Advisor: Stefanie Shattuck-Hufnagel Advisor: Aude Oliva

The Speech Communication Group has worked on a speech per- Deep neural networks excel at a variety of visual tasks. Cutting ception model based on acoustic cues to distinctive features called edge networks combine convolutional and recurrent networks landmarks. Landmarks can provide information on articulator-free to extracts rich high dimensional image features find key sequen- features of speech sounds (such as obstruent and sonorant) as well tial relationships from the input data. These networks are applied as distinctive features that specify place of articulation and voicing. to difficult tasks like visual question answering (VQA). However This speech information is valuable for sppech analysis and the current networks in VQA don’t have any attentional mechanisms Speech Communication Group is developing a speech analysis sys- which may boost performance by directing computations to more tem based on this approach. This system is nearing its completion; interesting image regions. We collect a novel dataset of human eye the SuperUROP research project will finish implementation by fixation positions on images shown after participants were asked integrating existing feature cue detection modules and develop- visual questions about the image. We then train deep learning net- ing remaining modules. The system will have applications to many works to fixate on informationally dense regions in input images areas including clinical speech analysis and automatic speech rec- evaluate our accuracy on the MSCOCO-VQA dataset and compare ognition. it with current benchmarks.

“I have had in an interest in programming for artificial intelligence “I took 6.869 and am taking 6.864 collected mobile eye tracking and music for a long time. These interests led me to my SuperUROP data in another UROP have worked with AWS and spent a summer project which works with a novel approach to speech analysis. I at a computer vision startup building their deep learning frame- have previously taken linguistics machine learning and signals work. I hope to gain more intuition behind how neural networks and systems which will be sure to help me. By the end of this proj- function. I am really excited that the project draws inspiration from ect I hope to learn about how speech recognition programs work.” behavioral data and I’m curious to find out how that affects other properties of the network.”

22 2016– 2017 Scholars Anita Liu William Lopez-Cordero MIT EECS Undergraduate Research MIT AeroAstro — Lincoln Laboratory and Innovation Scholar Undergraduate Research and Project: Speech production Innovation Scholar analysis for children with speech Project: REXIS Cover language impairments Advisor: Rebecca Masterson Advisor: Stefanie Shattuck-Hufnagel The REgolith X-ray Imaging Spec- My project will focus on using the trometer (REXIS) is the student col- acoustic cue system developed in the Speech Communication laboration instrument aboard NASAäó»s OSIRIS-REx asteroid sam- Group to analyze the speech of children. To gain a better under­ ple return mission. REXIS uses a 4x4 array of CCDs to collect X-ray standing of the mechanisms underlying language delay and dis­ fluoresced from the surface of Bennu. The REXIS CCDs are sensitive order in children, important acoustic landmarks in child speech to radiation and need to be protected during the 2.5 year cruise recordings elicited through non-word repetition tasks have been to the asteroid. To this end there is a radiation cover that sits on hand-labeled. Non-word repetition tasks have been shown to dis­ top of the instrument and is opened with a custom TiNi Frangi- tinguish children with speech language impairments in the past. bolt actuator upon arrival at Bennu. If the power to the Frangi- My project will build on previous work by labeling these speech bolt is not cut as soon as it actuates there is a risk of overheating samples for other landmark-related cues - specifically those of the actuator outgassing and contaminating the spacecraft. Thus place and voicing - and adding to the existing speech processing ground experiments need to be designed and performed using package to enable the automatic detection of landmark cues in REXIS spare hardware to provide confidence of the flight hardware the speech of both typically developing and atypically developing aboard OSIRIS-REx. children. “My name is William Lopez-Cordero and Iäó»m a current Junior “As a student studying Computer Science and Brain and Cognitive studying Aerospace Engineering at MIT. Most of my knowledge Sciences I am interested in how research in computer science can for the REXIS Cover SuperUROP comes from Unified Engineering illuminate the workings of the brain. Through this project I hope which I obtained from my sophomore year. I hope to learn techni- to learn about the landscape of speech processing technology. I cal skills that revolve around satellite engineering and important am excited to do work that will shed light on a still-elusive aspect research skills such as creating a poster presentation an oral pre- of human function and help children challenged by speech disor- sentation and a journal-style paper.” ders!”

Erika Lu Jordan Lucier MIT EECS — Lincoln Labs MIT EECS — Lincoln Labs Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: Flexible Object Project: Sensor Information Representations for Physical Scene Sharing in Self-Driving Vehicles Understanding Advisor: Samuel R. Madden Advisor: William T. Freeman In an ever more connected world, How can a vision system acquire common sense knowledge from data from mobile devices has emerged as an important resource visual input? Our goal is to infer physical object properties in unla- for answering questions the topography of our surroundings. beled videos by combining physics knowledge with machine Inferring maps (map-inference) and correcting them (map-correc- learning. We aim to create a system that, similar to a child, can tion) are two specific problems for which GPS traces from mobile observe a scene and use its knowledge of the physical world to devices are extremely useful. These traces are usually produced by predict how the objects might behave in different physical sce- commuters driving or biking on the road. Prior work on these map- narios. The system takes a two-step approach: it first recovers 3D ping problems exists, yet it is either unproven at large scale or pro- structural properties of the objects using convolutional neural net- prietary. This research will focus on designing and implementing works. It then uses a number of unit tests (e.g. evaluating stability) scalable adaptations of previous map-inference techniques and to refine its estimation by comparing the output of the physics a related map-correction algorithm. The implementations will be engine to the ground truth. based on top of existing systems such as PostGIS (Postgresql for geo-spatial data) and SpatialSpark. We will evaluate our applica- “I began working on my SuperUROP project last year as a regular tions on data from the Greater Boston Area, as we have an abun- UROP. From working on this project, I have learned a lot about current dance of data from this region. state-of-the-art computer vision research. It’s a very exciting field to be in at the moment and I’m looking forward to continuing this “I’m a rising senior and I play volleyball here at MIT. Last spring I project and exploring the many interesting directions we can take.” took a class on mobile devices and IOT, so this project is a natural followup to that work. I’ve been interested in this kind of work for a long time and I’m excited to have the opportunity to work on the project.”

2016 – 2017 Scholars 23 Jitesh Maiyuran Amin Manna MIT EECS — Analog Devices MIT EECS Undergraduate Research Undergraduate Research and and Innovation Scholar Innovation Scholar Project: Increasing Automation in Project: Developing a Classifier for Verification of Enumerated Data Parkinson’s Disease Patient Data Structures Advisor: Tomas A. Palacios Advisor: Armando Solar-Lezama

Machine learning (ML) is a powerful In a world dominated by technology tool in many industries, and medicine is no exception. Recently, the there is an increasing need for software transparency and correct- mPower mobile Parkinson’s Disease (PD) study allowed patients to ness. The industry standard is to write test cases that verify the use a smartphone application to answer surveys and complete correctness of code in most cases but an alternative is formal ver- tasks assessing dexterity, vocal tremors, and gait. Despite the avail- ification; which refers to the writing of formal proofs about desir- ability of data, there is no system capable of predicting whether a able invariants. Theorem provers such as Coq define tactics like person has PD based on these symptoms. Using the data collected “proof by induction” that can be applied to prove a theorem. The from the mPower study, this project will appropriately preprocess holy grail of formal verification is creating a “push-button” verifier the data and utilize statistical machine learning in the form of dif- that can prove any theorem but this is a difficult goal. My work ferent classification and learning methods in order to predict a will focus on developing a “push-button” verifier for theorems spe- patient’s diagnosis. cifically related to data structure invariants. Its conclusion will see increased adoption of formal proofs in the technology industry. “I am a Junior at MIT studying Computer Science and Economics. For my research, I am working on a machine learning (ML) model “I am studying pure computer science at MIT and have partic- that can predict the likelihood that a person has Parkinson’s Dis- ipated in the design and implementation of many software sys- ease from data collected on a mobile phone; I am very interested tems implemented in various coding languages. The construct in how machine learning can have a place in modern medicine. of language both computer and natural fascinates me and Throughout this project, I hope to learn more about different ML indeed this is why I am also concentrating in Linguistics. I am models and their implementation.” excited to apply the same rigorous analysis to computer lan- guages and I look forward to learning that in this SuperUROP.”

Jimmy Mawdsley Matt McEachern MIT EECS — Draper Laboratory MIT EECS — Lincoln Labs Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: Low Noise Terahertz Project: Teaching a Computer to Frequency Synthesizer in CMOS Understand Speech for a Carbonyl Sulfide Molecular Advisor: Jim Glass Clock Advisor: Ruonan Han Images and their corresponding spo- ken descriptions can be used to train computer systems to under- Integration of terahertz (THz) circuits in standard CMOS processes stand and learn new languages. Large amounts of this data can be has significantly progressed in recent years. As a result, there is an more easily acquired through an accessible iOS app. This app will increasing interest in silicon-based THz solutions for sub-millimeter presents users with images and allows them to speak and interact wave imaging, spectroscopy, and high-speed point-to-point com- with their iPhone as a means to convey what they are seeing in a munications. One compelling application of THz is a highly stable natural way. clock based on molecular resonance. Such a clock could, in theory, outperform current chip-scale atomic clocks on measures of stabil- “I have always been obsessed with mobile design and develop- ity, power consumption, size, and cost. The aim of this SuperUROP ment and have recently been interested in exploring Artificial project is to design a THz frequency synthesizer for the proposed Intelligence. I hope to use my skills in an impactful way and addi- molecular clock. The frequency synthesizer is a core component tionally develop a deep understanding of the underlying technol- of the molecular clock and must be designed for low power and ogy over time.” low noise operation in order to achieve the goal of part-per-trillion clock stability.

“I am very grateful for the opportunity to take on this SuperUROP project as part of the Terahertz Integrated Electronics Group. Though this project, I hope to develop my skills in THz RFIC design. I am excited to explore the high-frequency frontier and am par- ticularly interested in mmWave circuits for 5G communication sys- tems.”

24 2016– 2017 Scholars Amber Meighan Olivier Midy MIT EECS — MITRE Undergraduate MIT EECS Undergraduate Research Research and Innovation Scholar and Innovation Scholar Project: Securing Transactions Project: SigShare: Data with Blockchain Synchronization with Intermittent Advisor: Daniel Weitzner Mobile Web Connections Advisor: Michael Carbin We are living in an extremely data dependent society. We have a lot of With the rising prominence of mobile sensitive data that needs to be modified periodically and properly devices there has been an increased reliance on data retrieval via secured. There are plenty of current solutions that address how to the mobile web. In the absence of reliable connections the abil- do this in a private system. However our data is vulnerable as soon ity to update information on devices is lost thus hindering much as it leaves that trusted source. This study seeks to fix this problem of their functionality. This project explores designs for a mobile by showing that blockchains can be used to secure provenance of framework which allows mobile devices and their applications to sensitive medical data used by clinical trials. Hopefully this solution share data updates within the confines of a localized ad hoc net- can be used as a model to guard against data falsification and trial work. The implications of such a design in resource allocation misconduct by regulatory agencies and clinical trials companies. security and user privacy are brought to attention and an early implementation of the SigShare system will be presented. “I’m a Senior majoring in EECS. I’ll be exploring enterprise applica- tions for Blockchain technology as well as exploring where it can fall “This SuperUROP provides me the opportunity to explore the spe- short. I’m excited for the new experience and knowledge I’ll gain cific interests I have developed during my time as a computer sci- through my SuperUROP research. The applications of blockchain ence student at MIT - networking system design and back-end technology is wide and I can’t wait to better understand them soon.” systems. By developing the SigShare project I look to expand my depth of knowledge in these fields ultimately being able to use what I have learned to develop technologies which have impact both within and outside of academia.”

Clementine Mitchell Varun Mohan MIT AeroAstro — Lockheed Martin MIT EECS — Keel Foundation Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: Testing Gesture Control Project: Exploiting Parallelism and Performance Dependence on Optimizing Performance in OS Environment Presentation Kernels (Endogenous or Exogenous Advisor: M. Frans Kaashoek Conditions) Advisor: Leia Stirling Popular operating systems like Linux are written in C which does not provide easy mechanisms to exploit system parallelism. Fur- I aim to investigate the effect of environment presentation on gesture thermore it is desirable to write an OS in a language like Go that control performance in operation of the robotic arm on the ISS. Spe- provides simple concurrency primitives like mechanisms to spawn cifically performance of subjects in an exogenous environment (one transient threads as well as fast garbage collection which alleviates in which subject aligns with their external environment) will be com- the pains of freeing memory across multiple threads. Moreover my pared with an endogenous environment (one in which subject aligns research will delve into extending an implemented kernel in Go with themselves). The Oculus Rift virtual reality goggles will be set Biscuit by focusing on areas to optimize parallelism. In particular up with the Space Station Remote Manipulator System (SSRMS) sim- I will work on parallelizing many system calls like fork() and read() ulator to measure subjects’ performance in tasks testing their ability which perform computationally intensive work that is not cur- to operate the robotic arm. They will be tested in three control envi- rently parallelized in the Linux kernel. In addition I will also analyze ronments: exogenous with few environmental cues; exogenous with the overhead of spawning additional threads in the Go runtime. many environmental cues and endogenous. Hopefully this study will also be applicable to other gesture control systems. “I am a rising junior majoring in 6-2 who is very interested in computer systems. During my project I hope to extend an “Participating in a UROP in the Man Vehicle Lab for the past year thor- implemented kernel by exploiting system parallelism. Before- oughly sparked my interest in the effect of human factors on system hand I took 6.172 and enjoyed low-level optimizations so I design so I am really excited to learn more about how perspective feel optimizing a kernel during the project will be extremely impacts our ability to operate a robot via gesture control. I hope this exciting. I also wish to learn more about OS internals and information will help to guide the design of the optimal gesture con- get the feel of a much more long-term research project.” trol environment for both the robotic arm on the ISS and for future systems. 2016 – 2017 Scholars 25 Khaled Moharam Lucas Morales MIT EECS Undergraduate Research Undergraduate Research and and Innovation Scholar Innovation Scholar Project: RF design for Hydration Project: Contextual Learning with Measurement Integrated Least Effort Knowledge Advisor: Luca Daniel Networks Advisor: Joshua Tenenbaum Hydration monitoring is of promis- ing applications for individuals under In the field of artificial intelligence, high stress situations where dehydration and stress can cause most learning mechanisms are either inherently specialized or impairment of judgement or elderly patients with inappropri- have a flat knowledge base that makes them only useful when con- ately decreased or absent feelings of thirst. The ability to instan- fined to a single domain. These mechanisms are flawed as models taneously monitor hydration levels can be utilized for preventive of cognition because they have little capability for handling very intervention before any hospitalization is needed. The goal of the complex problems or specializing in multiple domains. This project project is to prototype a wearable device capable of measuring is to design a contextual knowledge system and augment learn- hydration levels in the body through RF measurements of water ing mechanisms to utilize this knowledge system in a manner that concentration in the wrist. In research we aim to develop efficient reduces the intractability of hard problems by creating implicit circuitry that can synthesize RF signals in the GHz range design relationships between items of knowledge. and develop antennas that are well matched with the system in study and data analysis techniques for inference of hydration lev- “How we as humans function has always had a place of interest in els. my mind. I intend to tackle tough problems in emulating human cognitive processes to fulfill this passion of mine. I’m excited to “As a student in my final year I’m looking forward to apply what I’ve pursue this challenge and push myself to understand the nature learned throughout my studies to a problem of promising oppor- of intelligence.” tunities for medical applications. Hydration measurement using RF technology provides challenges in careful RF design electromag- netic simulations and data analysis. The problem is challenging and of promising applications to the medical field.”

Rachel Morgan William Moses MIT AeroAstro — EECS MIT EECS — Keel Foundation Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: Nanosatellite Lasercom Project: Performance Engineering System in a Parallel Environment Advisor: Kerri Cahoy Advisor: Charles E. Leiserson

CubeSats (small satellites) have As Moore’s law ends and compute-in- become increasingly prominent in recent years due to their rela- tensive processes such as machine learning becomes mainstream tively low cost and improving scientific capabilities prompting a we must look to parallelism to allow our technological dreams to need for high rate communication capabilities. Traditional radio progress. Historically parallelism has been implemented with dis- frequency methods do not scale well to the size weight and power joint building blocks hacked together to make the whole thing run. constrained CubeSat platform and require large ground station The net result is weak parallel performance — especially compared apertures. Therefore free space laser communications (lasercom) with serial code! The goal of this project is to holistically integrate for small satellites is an area of active research due to the possi- parallelism into a programmer’s stack: modify parallel linguistics to bility of improving the data capabilities of small satellites signifi- make them both more optimizable and easier to use a compiler cantly. This project involves designing and prototyping an optical that understands parallel code to perform clever parallel optimiza- tranceiver for the Free-space Lasercom and Radiation Experiment tions on it and a low-level runtime system that is able to fully take which will demonstrate a laser communications crosslink between advantage of the hardware below it. two CubeSats. “I’m excited to be able to be at the forefront of parallel programming “I’m interested in the SuperUROP program because I think and see what sorts of linguistic and performance improvements free-space optical communications has a lot of potential to we can get. I’ve been interested in parallelism after developing a improve spacecraft communications especially if it can be high-level language for running physics simulations a few years demonstrated on a small platform. I’ve been UROPing in Prof. back. Since then I’ve done research on creating both fast compilers Cahoy’s lab since my freshman year and I’m excited to get and neural networks and I’m excited to see where this takes me.” more involved in the CubeSat projects she is working on.”

26 2016– 2017 Scholars Andrew Mullen Ayrton Munoz MIT EECS — Lal Undergraduate MIT EECS — Texas Instruments Research and Innovation Scholar Undergraduate Research and Project: Low-Power Biomedical Innovation Scholar Sensors and Machine Learning Project: Characterization of Advisor: Anantha P. Chandrakasan defects in GaN using first- principles calculations Stress-related disorders like migraines Advisor: Tomas A. Palacios and bruxism have symptoms that can cause consistent pain inhibiting productivity and quality of life. I A defect in diamond known as the nitrogen-vacancy center has will be working to develop efficient machine learning algorithms been recognized as a potential qubit candidate for use in quantum that can be programmed onto a biopotential sensor that are capa- computation. Although the center has been studied extensively ble of providing diagnostic information on electromyographic creating devices with diamond and integrating them into exist- signals. We desire understanding of how stress-related diseases ing technology has proven to be difficult. Our goal is to charac- manifest themselves in the electric signals of our facial muscles. terize defects in conventional wide bandgap semiconductors and By analyzing how the signals propagate through space and time determine if they can be used for quantum computing. Since qubit there is potential to understand these disorders in a computation- candidates must have luminescence which varies by spin sublevel ally relevant way. Once the electrical properties of the muscles we plan on using luminescence spectroscopy of GaN to determine are understood it could be possible to stimulate the muscles in a which types of defects should be considered. Then we will use closed-loop fashion to provide relaxation and relief to the patients. first-principles calculations to get a better understanding of the electronic structure of these defects and determine their viability “My name is Andrew Mullen and I am a senior studying EECS at as qubits. MIT. I’ll be developing machine learning algorithms for low-power sensors detecting electromyographic signals. I have been doing “I am currently a senior studying electrical engineering. I am inter- biomedical research at MIT since my sophomore year first at Bio- ested in using computational methods to determine properties mechatronics in the Media Lab and then neural engineering work of materials. I hope to learn more about both the theory behind at the Picower Institute. My intellectual interests lie at the intersec- first-principles calculations and how they can be applied to design tion of electronics and biology.” novel electronic devices.”

Battushig Myanganbayar Preksha Naik MIT EECS Undergraduate Research MIT EECS — Cisco Undergraduate and Innovation Scholar Research and Innovation Scholar Project: Parsing natural language Project: Architecture for Internet from annotated videos of Things: Optimizing Network Advisor: Boris Katz Performance Over Limited Data Semantic parsing is an approach Advisor: Vincent W.S. Chan to natural language processing In recent years there has been an which facilitates natural language explosive growth of the IoT network with an estimated 50 bil- interaction between human and machine. But current capabilities lion devices expected to join the network by 2020. A new archi- of semantic parsing are limited to basic tasks such as “Who is Ted tecture needs to be developed that can scale with the network. Cruz?” Significant amount of annotated data and hand tuning These scalability challenges open up numerous avenues for net- of features is required to capture all semantic complexities of work research. Some examples include (1) developing new tech- human language. In this project we will build a parsing model niques for network management and control to handle the needs based on videos and their short descriptions. By doing so this of large-scale dynamic networks (2) researching how to smartly semantic parser is both constrained by language grammar and deploy sensors to secure cyber-physical systems and (3) combin- physical interaction between objects in the video. The additional ing big data analytics with cognitive techniques to learn network information from physical interaction reduces the amount of behavior and operate networks. The expected focus of this project annotated data and makes it easier to build a general model with will be to see how sparse sampling of network parameters may be no hand tuning as laws of physical interactions are generic. used to infer network states and optimize performance. “I’ve always dreamed of building a machine that could learn all the complexities of natural language. I believe that the courses “I am excited by this SuperUROP as I will have the opportunity to in I’ve taken natural language processing and previous internship gain a more in-depth understanding of networking as well as learn focused heavily on machine learning techniques prepare me well about new advances in Internet of Things. Previously I worked on for my SuperUROP and I’m very excited to be closer to fulfilling my data transfer protocols for the CLARITY project an air quality net- dream.” work system developed within the MIT CEE department. I have also interned at Cisco Systems where I received exposure to concepts in software-defined networking.”

2016 – 2017 Scholars 27 Maya Nasr Demitri Nava MIT AeroAstro — Lincoln Laboratory MIT EECS — Morais and Rosenblum Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: SimSitu- MOXIE (Mars Project: Towards Large-Scale Data Oxygen Insitu Resource Utilization Discovery Experiment) Advisor: Samuel R. Madden Advisor: Jeff Hoffman The Data Discovery group aims to SimSitu - SimSitu: A multi-physics simulation framework for design provide a data discovery system that facilitates locating relevant control and analysis of the MOXIE experiment and other ISRU data among thousands of data sources. With thousands of data processing plants This SUPER UROP will focus on enhancing the sources spread across disparate databases and files analysts often capabilities of the SimSitu a MATLAB/Simulink based program for spend more time searching for and identifying relevant data to modeling space insitu resource utilization processing plants. The answer the questions at hand than analyzing it. With the data dis- primary case study for this will be the MOXIE experiment that will covery system the group wants to simplify the process of finding produce oxygen aboard the Mars aboard the 2020 rover. The stu- relevant data minimizing an analyst’s time searching for data. dent will study processing plant controls fault tolerance and work on expanding these capabilities to larger ISRU systems. Knowledge “I’m a course 6 senior interested in learning more about data- of with control systems and chemical engineering plants is bene- base internals. Through my SuperUROP project I hope to ficial. Skills with MATLAB Simulink and/or process modelers are solve and gain more exposure to modern data problems.” desired.

“I’ll study processing plant controls fault tolerance and work on expanding these capabilities to larger SRU systems.I’ve also worked before in the MVL and I was interested in projects in the Humans in Aerospace area so I think that this will strengthen my experiences especially in Controls and Space Systems.It’s an amazing opportu- nity to be able to contribute to something that will launched on the 2020 rover to Mars.”

Weerachai Neeranartvong Linh Nguyen MIT EECS — Angle Undergraduate MIT EECS — Seven Bridges Genomics Research and Innovation Scholar Undergraduate Research and Project: Model-based Transfer Innovation Scholar Function of Arterial Blood Project: Analyzing mutational Pressure (ABP) to Intracranial signature in somatic cancer Pressure (ICP) Advisor: Ana Bell Advisor: George C. Verghese All cancers carry somatic mutations. Intracranial pressure (ICP) is the pressure inside the brain tissue The mutations are caused by “mutational processes” characterized and cerebrospinal fluid. It provides information about intracra- by a disproportionate amount of mutation types. Using whole-ge- nial dynamics and helps clinical decision-making. Our project is to nome sequences data of somatic cancers from 560 patients we study the transfer function between arterial blood pressure (ABP) would like to decode the mutational processes encoding the and ICP, while correcting for respiratory effects. We will also look for mutations. Understanding the mutational signatures will help the best fit to the ICP measurements using waveforms generated understanding the biological processes causing such driver muta- by a physiologically motivated lumped-parameter model, when tions therefore helping us to find more effective and personalized the model is driven by the measured ABP signal. Examining values treatment to the patients. and trends in the estimated model parameters will help us deter- mine the patient’s intracranial state. “I am a senior studying Mathematics and Computer Science and I always enjoy working on problems with multidisciplinary natures. “I’m a course 6-2 and 18 junior passionate in mathematics. I became Based on the work I have developed from the summer I have interested in this project as Prof. Verghese presented to me how gained tremendous understanding of cancer genomics and I signal processing can be applied to healthcare problems and bio- would like to continue the project for the coming year. I believe medical signals. This project will be a great opportunity for me to the skill I learn from SuperUROP would tremendously help me con- explore the intersection between mathematics, signal processing, tribute to the understanding of genomics.” and biomedicine.”

28 2016– 2017 Scholars Timothy Nguyen Ebenezer Nkwate MIT AeroAstro — Pratt and Whitney MIT EECS Undergraduate Research Undergraduate Research and and Innovation Scholar Innovation Scholar Project: Synthetic Gene Circuits for Project: Design Optimization Cardiomyocyte Proliferation and of Propulsive Stream Ducts In Heart Disease Treatment Modern Turbofan Engine Systems Advisor: Timothy K. Lu Advisor: Edward Greitzer Organisms monitor their environ- Although turbofan jet engines have been well studied, particularly ment and respond to various factors with a variety of complex the complex turbo-machinery that comprises the core engine, one behaviors including but not limited to gene expression, cell mor- area that is still not well characterized is the fan bypass duct which phology and motility regulation of the cell cycle and growth and surrounds the core. The potential to improve the propulsive effi- protein secretion. The circuits that control such responses are ciency of the engine by decreasing losses in these ducts provides usually genetic in nature and have evolved over time to augment an opportunity for useful contributions to both commercial and the fitness of the organism. Synthetic gene circuits are systems military aviation. The aim of this project is to explore the scope for designed to perform user-defined functions in a predictable and improvement by assessing the aerodynamic losses within these reliable manner. This project aims to engineer genetic logic gate ducts and to develop suggestions for improvements. This will be and circuits that are able to detect heart state and stimulate pro- done through wind tunnel scale model experiments and, if there is liferation of cardiomyocytes. By stimulating proliferation of these time, though numerical simulation. cells we will be decreasing the adverse effects that follow the onset of various heart diseases. “I’ve had experience with industry and research and I feel like this opportunity is a perfect blend of the two. I’m excited to apply the “The body’s ability to efficiently control so many regulatory path- knowledge I’ve learned to real world problems and I hope to get ways with vast dependences has always intrigued me. Hence, better insight into what career path I want to follow. I’m looking I aim to apply physiology, analog circuit design, and algorith- forward to solidifying my foundation in this subject material since mic principles in order to understand how to control these I have a lot of interest in the fields of propulsion and aerodynamics.” systems in their disease state and restore optimal function.”

William Noble Alexander Nordin MIT EECS — Fano Undergraduate MIT EECS — Landsman Research and Innovation Scholar Undergraduate Research and Project: Fast Segmentation of Innovation Scholar Large Neuronal Subvolumes using Project: Hydration Monitoring in a Concurrent Watershed wearable wristband Advisor: Nir N. Shavit Advisor: Martha L. Gray

A convolutional neural network The hydration project is focused on (CNN) framework has been developed to enable high-perfor- developing the technology missing or too invasive for daily use for mance image processing on highly parallel machines. It is being reliable and physiologically meaningful hydration tracking with an used to pre-process scanning electron microscope (SEM) images aim of optimizing hydration and avoiding dehydration. We created of a mammalian brain for automatic segmentation of the con- the project at MIT with a primary focus on the substantial need for stituent neurons. The software targets multicore commodity CPU improved hydration management in the elderly but with a view shared-memory systems instead of large clusters or expensive GPU to the needs in many sectors and the broader population. We are or ASIC hardware, in order to make high-throughput image seg- currently carrying out clinical testing in Madrid and Boston of two mentation more accessible to researchers. To facilitate use of the novel non-invasive technologies in a non-miniaturized prototype framework, an interface to a popular neural network API front-end yet have designed both technologies to function on miniaturized called Keras will be implemented. This will enable faster iteration architecture for a 24/7 wearable format focusing on comfort and on CNN models for use in the image processing pipeline, by our reliability of the underlying measurement. team as well as the neuroscience and machine learning commu- nities in general. “I’m participating to learn about the process regarding creating a new project and my fascination with the work I’ll currently be “This field of research is incredible, and being able to contrib- doing.” ute to the eventual modeling of mammalian brains is really cool. I’ve always had a fondness of language/API design and sys- tem design, and this project sits at the intersection of the two.”

2016 – 2017 Scholars 29 Byungkyu Park Rajeev Parvathala MIT EECS Undergraduate Research MIT EECS — Lal Undergraduate and Innovation Scholar Research and Innovation Scholar Project: Developing Tools for Project: Alignment of Elastically Building Accessible Mobile Apps Deformed Electron Microscopy Advisor: Lalana Kagal Images Advisor: Nir N. Shavit This project involves designing and developing relevant libraries and The Computational Connectonom- toolkits to enable the development of accessible mobile apps. ics group is trying to take huge volumes of detailed SEM images Handheld devices such as mobile phones tablets and smart from mouse brains and use computational methods to learn about watches are rapidly replacing desktops and laptops as primary neuron interconnections from the images. There are many steps communication and computation platforms for many people. With involved in this process the first of which is image alignment. almost one billion people with disabilities in the world ensuring Essentially because the brain slices are extremely thin you end that apps for these handheld devices are accessible by people with up a detailed 3-D visualization of the mouse brain such that there disabilities are becoming more and more important and critical are layers of 2-D images that are overlaid. I plan on finding a fast for emergency situations. The project is looking to develop some effective way to find identical features between the two overlaid tools that can be helpful for developers who want to build accessi- images made more difficult because the transformations between ble mobile apps. In addition to building a toolkit the project also images are nonlinear. Our plans to approach this problem include focuses on possibly developing code libraries that can be widely utilizing optic flow algorithms and convolutional neural networks. used by developers. “I really wanted to work in an area that would be able to integrate “My name is Byungkyu Park and I am a senior majoring in 6-3. my interests in machine learning and low level programming/ Building from my previous experience with iOS development I performance engineering and this project seemed perfect for my would like to learn more about Android development. The most goals.” exciting thing about this project is that it will actually be a big help for disabled people; more accessible apps will be available for peo- ple who really want to use mobile apps but having a hard time using them because of disabilities.”

Jeanine Pearson Gailin Pease MIT EECS Undergraduate Research MIT EECS Undergraduate Research and Innovation Scholar and Innovation Scholar Project: Next Generation Project: Programming Language Humanitarian Technologies Use in Julia Advisor: Lalana Kagal Advisor: Jiahao Chen

In humanitarian crises information is New languages come with lists of key to ensuring that disaster response features touted as tools to help pro- efforts occur effectively and efficiently. However since information grammers be productive and solve problems. In Julia multimeth- has to be acquired from a variety of different sources at different ods and optional type annotations are two such features. However times it can be hard to obtain when needed. This project deals there is little work on how programmers actually use the tools a with designing and developing a notification service that monitors language gives them. Understanding how programmers leverage information essential for relief operations and workers provided by language features over the course of developing software and the different parts of the United Nation Office for the Coordination of extent and context of feature use can provide insight into what Humanitarian Affairs (UN OCHA). This includes contact information Julia does well as a language and where it or future languages from the Humanitarian ID API content about disasters and other could improve. I will continue developing an analysis library for events from ReliefWeb and reported humanitarian aid contribu- Julia code and apply that library to find out how users approach tions from Financial Tracking Service (FTS). writing Julia code.

“I’m interested in the ways technology can be used to make “I am studying computer science and am interested in computer peoples’ lives better and I’m excited to do that with CSAIL systems engineering. The Julia group provides a unique oppor- and the UN. After 5 internships I’m glad to have the chance to tunity for the study of programming language use because we try something new and work in academia. I think that work- can look at code by real users (the Julia ecosystem has hundreds ing with the Humanitarian ID and ReliefWeb tools will be a of packages written by users around the world) but the language great way to tangibly help real people while the collabora- itself is still growing and changing so understanding its use so far tion with CSAIL will help me find out what research is like.” can be of real help.”

30 2016– 2017 Scholars Navil Perez Marcos Pertierra MIT BE—Microbiome — MIT EECS Undergraduate Research Undergraduate Research and and Innovation Scholar Innovation Scholar Project: Coding the Tax Code: Project: Mucus Mediated Quorum Regulations to Formalism Sensing in Pseudomonas Advisor: Una-May O’Reilly aeruginosa Advisor: Katharina Ribbeck The STEALTH Project aims to model and represent regulations in the IRC Efforts have been made to create a blueprint of the human micro- simulate transactions and apply AI techniques to optimize tax out- biome by characterizing the microbial populations ubiquitous to put and risk of audit. Thus the result is a system that can predict each part of the human body. A significant amount of progress has new tax evasion strategies that might arise with changes in regu- been made in cataloging the microbiome; however cellular inter- lation. The first component of the system requires a formal repre- actions within these microbial communities have remained largely sentation of regulations. It would seem impractical to directly read unexplored. This research will investigate how host induced fac- and convert a large number of regulations (human-readable text) tors mainly mucus affect quorum sensing cellular communication. to machine-readable code that can then be used for simulation. Breakthroughs in understanding the role mucus plays in pacifying Hence the main focus of this project is to develop an automatic microbe-microbe competition can allow us to exploit mucus in the parsing system for translating these regulations into a formalism. development of novel infection therapeutics. Our strategy is to experiment with NLP algorithms develop such a system to perform this parsing and translation. “My first experience with laboratory biology was an introduction to the microbiome. I have since remained fascinated by the mag- “I am participating in the SuperUROP program because I want to nitude of the effects of these microscopic organisms can have on take part in exciting research and explore innovative techniques in human health. Today I am happy to study how the host environ- the field of Natural Language Processing. Although I do not have ment modulates interactions among the organisms comprising much experience in this field I hope to learn as much as possible the microbiome.” before and during the project; I will also be taking 6.806 in the Fall.”

Huy Pham Michael Picchini MIT EECS — Slaughter MIT AeroAstro — Draper Laboratory Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: Efficient reliable testing of Project: Robotic Arms for the complex software systems SPHERES Satellites Advisor: Armando Solar-Lezama Advisor: Alvar Saenz-Otero

Software testing is a critical step I will be working on the SPHERES in every software development process as it provides important ARM project, which is a robotic arm for small satellites on the Inter- information about the software quality and risk of failure. Even national Space Station (ISS). My research project will interface a for simple software components, it is infeasible to do exhaustive robotic arm with SPHERES for the purpose of enhancing the capa- testing since the number of possible test cases becomes practi- bilities of the satellites to further interact with the environment cally infinite. Software developers usually need to manually write and other SPHERES. I will start by designing the robotic arm to numerous test cases in such a way such that they cover all import- ISS standards, which includes adhering to all safety measures like ant behaviors, including corner cases. This task is often tedious and proper building materials, hardware, and mechanical and elec- error-prone to do by hand. Our project aims to explore different trical design. Then, I will interface the arm to properly work with automated testing techniques and apply them in real-world cases, SPHERES. Finally, I will develop equations and simulations to and ultimately create a new, efficient and reliable technique for model the dynamics of the arm in a microgravity environment, testing various complex software systems. and analyze the results, as well as run physical tests on the Space Systems Lab’s flat floor facility. “I’m very excited about this project because it aligns with my inter- ests in computer systems and mathematics. Previously, I worked on “I am currently a junior studying aerospace engineering and work- the StreetScore project at MIT Media Lab’s Camera Culture Group ing on building a robotic arm for small satellites on the ISS called where I used machine learning and computer vision to quantify SPHERES for my SuperUROP. I have been working on this UROP the dynamics of the built environment.” since my freshman spring semester, and I am excited to invest more time and funds to take the project to the next level. I hope to learn how to design, build, and finalize a system from the ground up.”

2016 – 2017 Scholars 31 David Pineiro Varot Premtoon MIT EECS — Hewlett Foundation MIT EECS — MITRE Undergraduate Undergraduate Research and Research and Innovation Scholar Innovation Scholar Project: Expanding the START Project: ClearScope: Detection and Question Answering System Policy Enforcement with Dependency Parsing and Advisor: Howard Shrobe Statistical Methods Advisor: Boris Katz ClearScope is a precise comprehen- sive configurable and efficient provenance tracking system for START is a web-based natural language question answering sys- Android mobile devices. ClearScope will dynamically track the tem developed at CSAIL InfoLab. Aiming for high precision START provenance and flow of information through all system layers is largely rule-based and suffers from both low recall and the need making currently opaque computing systems transparent by pro- for human annotation to build its knowledgebase. This project viding high-fidelity visibility into component interactions while explores the use of dependency parsers to parse natural texts into imposing minimal performance overhead. This tracking capability START’s ternary expression and automatically build the knowl- will allow ClearScope to determine when the Android device has edgebase. Other natural language processing and machine learn- been breached by an advanced persistent threats and other similar ing methods will be examined as well. Matching algorithms will be high risk threats. developed to link the appropriate information in the knowledge- base to user’s question. By fitting modern high recall technologies “Growing up in Cuba I got to see first hand the effects of absence into START framework we aim to design a high precision QA sys- of security on individuals. As a result I have taken security classes tem that is capable of indexing various data sources automatically. and am part of the CyberSecurity@CSAIL group. I hope to learn more about machine learning algorithms to classify breaches. “I will be improving START Question Answering system using a Merging big data analytics with computer security is fascinating statistical parser and other ML techniques. My interest has always so I am looking forward to exploring what lies between these two been in NLP the intersection of computer science and linguistics. powerful and important tools.” Question answering is a fun NLP problem because it is technically challenging and has a potential to change how we communicate with information. Through this project I hope to become both a better researcher and a better engineer.”

Rishad Rahman Shraman Ray Chaudhuri MIT EECS — Lincoln Labs MIT EECS Undergraduate Research Undergraduate Research and and Innovation Scholar Innovation Scholar Project: Optimizing Neuron Project: Eliminating the Gap Segmentation for Connectomics Between Classical and Multiscale Advisor: Nir N. Shavit Measures of Map Distortion Advisor: Justin Solomon “Connectomics” refers to the study of connections in the human brain. A simple problem that still doesn’t have a general purpose solu- High-resolution EM images of brain tissue allow us to reconstruct a tion is approximating a surface with a planar mapping. Applica- 3D map of the brain (neurons synapses) which can lead to greater tions which require a grid to map onto a surface introduce some understanding of brain physiology and disease. However the vol- distortion and the parameterization probably has an associated ume of images is on the scale of petabytes. My project aims to metric to minimize the impact of that distortion. A disk has zero increase the performance of “segmentation,” the multi-step pro- curvature everywhere so a sparse Gaussian curvature distribution cess to extract neurons from images with novel algorithms and will assist with the parameterization. We generate a sparse distri- their high-throughput implementation on state-of-the-art hard- bution is via convex optimization by looking at the transportation ware.” cost of changing the curvature distribution defined by the geode- sic distances and movement of curvature between pairs of points. “Research gets me out of the bubble of computer science. It’s Another important technique which is involved in our optimiza- refreshing to see an interdisciplinary approach to solving prob- tion problem is that of regularization to enforce that our distribu- lems in our world and to challenge myself to contribute alongside tion is indeed sparse. phenomenal faculty at MIT.”

“My SuperUROP project involves geometric data processing to analyze distortion in graphical mappings on shapes. This project will provide me with experience testing optimization methods I’ve studied experimenting with them to observe which parameters work best for the problem at hand. I love the fact that I am building upon my advisor’s research which gives me confidence in having the resources necessary to succeed.”

32 2016– 2017 Scholars Erin Reynolds Daniel Richman MIT CEE — Undergraduate Research MIT EECS — Texas Instruments and Innovation Scholar Undergraduate Research and Project: Bioengineering Yeast for Innovation Scholar Heavy Metal Cleanup Project: Physical Layer Security in Advisor: Angela Belcher RF Communication Systems for the Internet of Things Bioremediation using bioengineered Advisor: Anantha P. Chandrakasan yeast has the potential to be an inex- pensive, environmentally benign, and efficient treatment tech- The Internet of Things connects a variety of new embedded sys- nology. Yeast has been shown to naturally accumulate a variety tems to the Internet, offering greater opportunities to access infor- of metals, and bioengineering techniques can be used to greatly mation in applications such as wearables, smart cities, and health enhance the metal accumulation processes of yeast. We plan to care, but also presenting a unique set of security challenges. Our develop two strategies for enhanced bioremediation: 1) internal research will focus on a novel approach to securing these devices metal accumulation by over expression of metal transport proteins and the data they transmit: guarding the physical network layer. and 2) hydrogen sulfide precipitation of metals on the cell surface. We will develop and analyze new techniques including with- in-packet frequency hopping, RF fingerprint concealment and “I learned most of the basic techniques such as molecular cloning, compressed sensing. These methods can provide both quantifi- culturing, ICP-MS, microscopy, etc. Now I am ready to take a big- able security benefits and potential transmission optimizations. ger part in planning experiments and analyzing data. I am excited After developing and optimizing our frequency hopping protocol about this project because I get to manipulate an organism at the we will demonstrate it in an end-to-end wireless transceiver plat- genetic level and the application of this project is to make more form with off-the-shelf components. efficient and sustainable heavy-metal treatment technologies.” “Designing and implementing security into the physical layer of wireless communications will be a new approach for embed- ded devices and I’m pleased to work on it in depth for a whole year. My previous studies include modern cryptography and computer systems and I’ve contributed to a range of embed- ded software projects. Embedded design too often treats secu- rity as an afterthought so I’m excited about systematizing it.”

Maria Ximena Rueda-Guerrero Luzdary Ruelas MIT EECS Undergraduate Research MIT ChemE — Undergraduate and Innovation Scholar Research and Innovation Scholar Project: Automatic analysis Project: Alternative of speech from typically and Antisolvent Crystallization atypically developing children of Diphenhydramine with Advisor: Stefanie Shattuck-Hufnagel Functionalized Iron Oxide Nanoparticles In this project we will analyze typi- Advisor: Allan Myerson cally and atypically developing children’s speech using the land- mark/acoustic cue system developed by the Speech Communi- The global shift towards sustainable technology has motivated cation Group. Landmarks are robustly-detectable locations in the research for waste minimization in chemical processes such as signal that indicate classes of speech sounds. Additional acoustic crystallization. Crystallization is used to form a pure crystal from a cues near landmarks specify other distinctive features related to saturated solution. Currently antisolvent crystallization is the most place of articulation and voicing that define each sound. The reali- widely used technique but it fails to meet green chemistry specifi- zations of landmarks and other acoustic cues are strongly impacted cations by adding more solvent to the original solution ultimately by prosodic events such as phrase boundaries and phrase-level increasing waste. Using functionalized iron oxide nanoparticles as accents. We have applied this feature-cue-based approach to child an alternative to antisolvent crystallization addresses waste prob- speech elicited by non-word repetition tasks with hand labeling of lems since the particles have magnetic and tunable properties the landmarks and the next steps will be to develop a software for making separation easier and allowing their reuse. My SuperUROP automatic detection of landmarks. project will focus on developing a crystallization and purifica- tion method for a diphenhydramine system using functionalized “I decided to participate in SuperUROP to engage in a long research nanoparticles. project while also receiving guidance in performing research. I had participated in this same project as a UROP student and I wanted “SuperUROP allows me to drive the work and lets me devote myself to continue it through the SuperUROP program too. I hope to learn to research. My project is to change the solubility of diphenhydr- more about linguistics and applications of machine learning for amine in solvents by adding functionalized iron oxide nanoparti- speech recognition algorithms.” cles. My background provides insight for beginning but crystalli- zation is new to me so I hope to learn more about the field. This project excites me because it addresses issues from environmental factors to the manufacture of drugs..” 2016 – 2017 Scholars 33 Shinjini Saha Ajay Saini MIT EECS Undergraduate Research Undergraduate Research and and Innovation Scholar Innovation Scholar Project: Deja Vu: Constructing Project: Using Online Data to Apps from Cliches Predict Startup Success Advisor: Daniel N. Jackson Advisor: Tauhid Zaman

If you look at most websites even In recent years technology startups vastly different websites like Face- have both become very prevalent in book Youtube or Amazon you’ll find that they have a lot of things society and attracted the interest of many researchers. The ques- in common: a profile with user information a news feed a rating tion of how to predict the probability of success of a startup is system instant messaging etc. But right now if someone wants crucial to problems in fields such as portfolio optimization and to create a new website even if they want their website to have business strategy. In previous works researchers have found that these common reused features (conceptual clichés) they have to by using multiple data sources to build interaction networks it is implement them from scratch. The idea behind DEJA vu is to create possible to both understand and model an underlying system in a platform where these conceptual clichés can be integrated with- a way that yields powerful predictions about the system. The goal out having to do any extra work. It will be a platform for end-users of my SuperUROP is to use online data to build a network-based who have no coding background to create a novel web applica- model of the startup ecosystem that is able to make probabilistic tion with these common features in an easy intuitive way without predictions about whether or not a startup will succeed in a given writing a single line of code. time period.

“I have been working on this project for the summer and it has “My interest in predictive analytics and machine learning started been a lot of fun and I’ve learned a lot. I will continue this project years ago and has since grown through multiple UROPs and for the SuperUROP because I can gain even more different expe- classes such as 6.867 and 6.437. I want to participate in the Super- riences due to the evolving nature of the project and also from UROP program in order to both hone my research skills and have how the SuperUROP will prepare me on presenting my work to the the opportunity to create a predictive model that is impactful on general audience. I’m looking forward to continuing working on the world.” this project during the semester!”

Manjot Sangha Valerie Sarge Undergraduate Research and MIT EECS — Quick Undergraduate Innovation Scholar Research and Innovation Scholar Project: Predicting DNA Functional Project: An Energy-Efficient FPGA Elements using Genome Computer Vision platform for Real- Topological Features and Deep time Object Detection Learning Advisor: Vivienne Sze Advisor: David K. Gifford The purpose of my SuperUROP proj- The prediction of transcription factor binding sequences in DNA is ect is to write an efficient and accurate FPGA, GPU, and ARM sys- an important problem in computational biology with implications tem for an existing super-resolution algorithm. This system will for many biological phenomena. Current approaches have used receive HEVC-encoded video files as input, and output higher-res- ChIP-seq data to learn a representation of a given transcription olution, upsampled images. After postprocessing, these frames factor’s binding affinity. One such method is the k-mer motif and will be ready to display. Super-resolution as a technology has the alignment clustering (KMAC) algorithm to produce k-mer set motif potential to improve users’ computer graphics and enable the use (KSM) representations. However the use of ChIP-seq data is rela- of high-resolution (4K or 8K) screens in many contexts without a tively expensive because a new dataset has to be derived for each loss of quality in viewing existing lower-resolution content. transcription factor. In order to improve this we propose to adapt the KMAC/KSM approach to use DNase-seq data which can be “This past year, I enjoyed taking 6.111 and 6.375, both classes on treated as multiplexed ChIP-seq data in order to produce binding FPGA design. Through this project, I hope to gain more experi- site representations for multiple transcription factors from a single ence with hardware description, realizing algorithms in hardware, DNase-seq experiment. and optimizing digital architectures. I’m also excited to work on super-resolution; projects like this one could enable the adoption “I am participating in SuperUROP to get more hands on experience of high-resolution screens in many devices.” in a research settings. I am a course 6 student but have also done a lot of work related to biology including many terms doing wet lab research. This computational biology project looks like an exciting way to marry these two interests.”

34 2016– 2017 Scholars Mehmet Tugrul Savran Alisha Saxena MIT EECS Undergraduate Research MIT EECS Undergraduate Research and Innovation Scholar and Innovation Scholar Project: Algorithmic Clustering Project: Developing Novel and Analysis of Spatial Methods for Robust De- Organization of Chromosomes identification of Electronic Health Advisor: Caroline Uhler Record Data Advisor: Roger Mark Spatial organization of DNA is known to be pivotal for gene regulation. Thus understanding 3-D organi- In the USA the HIPAA Privacy Rule restricts exchange of medical zation of genetic material is essential in understanding the func- data containing protected health information (PHI) defined as tioning of gene regulation. Recently developed Hi-C techniques any information that might be used to identify the individual(s) provide genome-wide average contact frequency data. We will from whom the data were collected. However much of the data develop convex optimization algorithms to “transform” Hi-C data collected from hospitals for research purposes does contain PHI. and use it to build models of 3-D organization of genomic material. The process of removing this PHI from free-text medical records is We will take a shape-packing approach and model the spatial orga- very tedious and error-prone. Existing automated de-identification nization of chromosomes as a minimum overlap ellipsoid problem software is inefficient and limited in applicability across different constructing topological domains. We will infer noisy distance datasets. Hence we aim to build a modularized de-identification measures between these domains to understand the reachability package that robustly de-identifies medical records in accordance among other domains. The process will be repeated for different with HIPAA standards and is widely applicable easy-to-use and cell types to characterize differences in gene regulation. efficient.

“I am amazed by how computer science aids in tackling complex “I’m fascinated by the intersection of computer science and med- problems especially in genetics research. When I took 6.041 I got icine and am excited to work on a project that can augment the exposed to stochastic modelling of complex systems and loved it. data-driven approach to healthcare research. I’ve gained experi- Already trained in programming through internships and classes ence with big data & machine learning as an intern at Google Uber I now have the chance of combining curiosity theory and appli- and Apple and data security & privacy at NASA and Univ. of Wash- cation in a comprehensive research project thanks to SuperUROP.” ington so I hope to apply and enhance my skillset as I work in the Lab for Computational Physiology.”

Divya Shanmugam Yinghua Shen MIT EECS — Lincoln Labs MIT EECS Undergraduate Research Undergraduate Research and and Innovation Scholar Innovation Scholar Project: Computational Project: Developing Compressive diagnostic aids for biomedical Algorithms for Large-Scale instrumentation data Metagenomic Data Analysis Advisor: Jiahao Chen Advisor: Bonnie A. Berger While medical records have all been Metagenomic datasets are exponentially increasing in size at a digitalized nowadays the amount of patient data that can be rate that outpaces computing power. This project focuses on using usefully processed and analyzed using available software tools compression to mitigate the computational burden of metage- is greatly limited. This is often caused by a lack of techniques to nomic datasets. Compressive genomics is based on the redun- determine indicators and trends in the data and inadequate dancy of the genome and the project aims to exploit this redun- understanding of the domains that concern physicians most. How- dancy on a metagenomic level. These compressive methods will ever such data contains useful clues that could help doctors make dramatically accelerate the meta-genomic pipeline and allow better informed decisions and improving medical care for patients. researchers to deriving tangible results from increasingly large Therefore I would like to develop new computational diagnostic datasets efficiently. aids for medical data.

“My name is Divya Shanmugam and I’m a senior majoring in “I am a senior in 6-3 and I will be developing computational diag- Course 6-3. I’ve spent the past couple of years loosely inter- nostic aids for biomedical instrumentation data in my SuperUROP ested in the intersection of algorithms with the life sciences. project. This project sparks my interest because I am passionate Much of my past work has been geared towards this inter- about data engineering and exploring new ways to make use of est and the same can be said about this SuperUROP. I hope poorly-utilized data.” to develop a strong framework for research this semester and sharpen my ability to approach open problems this semester!”

2016 – 2017 Scholars 35 Cooper Sloan Hyunjoon Song MIT EECS Undergraduate Research MIT EECS — Hewlett Foundation and Innovation Scholar Undergraduate Research and Project: Modeling and Prediction Innovation Scholar of Bus Arrival Times Project: Internet of Threats: Advisor: Jiahao Chen Analysis of an Internet of Things Botnet Being able to accurately predict arrival times and delays is a key to Advisor: Howard Shrobe optimizing network traffic. In the In 2014 Eugene Kaspersky who is the CEO of a world-renowned context of public transit systems accurate prediction of bus arrival cybersecurity company named Kaspersky Labs said that Internet times reduces passenger wait times and improves efficiency. This of Things (IoT) essentially means Internet of Threats. As the number project focuses on the Massachusetts Bay Transportation Author- of connected smart devices accelerates a rapidly growing number ity dataset which contains several years of bus transit data. The of them will be subject to many attacks geared to obtain criminal goal of this project is to used advanced statistical models as well profit. Before IoT is fully realized it is imperative to address a num- as machine learning techniques to accurately predict bus arrival ber of security and privacy challenges prevalent in these devices times. as quickly as possible. We will solely focus on the latest IoT botnet malware called Mirai and extensively analyze the behaviors of the “I’m using Boston transit data to try and predict bus arrival times. running botnet using infiltration techniques in an effort to find -tar I’m hoping to gain experience in data science specifically machine geted vulnerabilities in IoT devices and understand the motivation learning techniques on a real data set. After taking 6.036 I got inter- behind these types of attacks. ested in machine learning algorithms and I’m looking forward to putting them into practice.” “I’m Hyunjoon Song a senior majoring in Course 6-3. As part of the SuperUROP program I will be working with Dr. Howard Shrobe. My project is to perform an insightful analysis of the Mirai botnet in order to add a general understanding of an IoT botnet. What excites me about the project is that many people do not under- stand the potential impact of malicious attacks using IoT devices.”

Ali Soylemezoglu Mayuri Sridhar MIT EECS — Mason Undergraduate MIT EECS — Draper Laboratory Research and Innovation Scholar Undergraduate Research and Project: Using Deep Learning to Innovation Scholar Classify Cell Images in order to Project: Exploring User and Item Detect Cancer Reliability to Minimize Regret in Advisor: Caroline Uhler Recommendation Systems Advisor: Guy Bresler Neural networks are the state of the art when it comes to image classification. We intend to exploit the Recommendation engines are one of the most widely used applica- success deep learning has had in image classification in an attempt tions of machine learning. For example we can imagine I’m brows- to classify images of cells to detect the early onset of cancer. Cur- ing Amazon for some new shoes. Perhaps a new sale has recently rently features are extracted manually. We attempt to use deep gone up from a seller who has previously sold to buyers similar learning to first automatize the feature extraction process and to me — so Amazon chooses to recommend this sale. However then classify cell images. Furthermore we will be investigating this doesn’t take into account the value of the seller — for instance techniques such as Multiple-Instance Learning (MIL) in classifying maybe the seller has very little history and I only want to buy from these images. At a high level we will be interested in the follow- sellers that I deem trustworthy”. It also ignores whether the buyers ing two end goals: a) binary classification of cells (i.e. cancerous or who are similar to me make truly reliable recommendations. My non-cancerous) and b) using manifold learning to learn how can- project focuses on developing a more accurate recommendation cer progresses. engine that focuses in on different user and item intrinsic values and using these to minimize regret over recommendations for all “Having participated in several UROPs I feel prepared to commit users in the network. to a year-long independent projectI am excited to be working on a project at the intersection of cancer research and ML. It will give “I’m a rising senior majoring in computer science and mathemat- me an opportunity to apply my knowledge of ML on a very import- ics. I’ve always loved research - for two years of high school I did ant topic. I hope to learn more about cellular biology further my research a local university in computational biology. I love learning ML knowledge and gain experience in independent research.” about the newest work in the field and working with the people who make it happen. I’m excited to spend the next year learning more about machine learning and I hope that my work will con- tribute to the field as a whole.”

36 2016– 2017 Scholars Rahul Sridhar Sanjana Srivastava MIT EECS — Lincoln Labs Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: Using Image Saliency Project: Improving and to Reduce Runtime of Image Augmenting LAVA, a Vulnerability Classification in Deep Neural Injection System Networks Advisor: Dennis M. Freeman Advisor: Tomaso Poggio

There is a pressing need for a way to evaluate the effectiveness of Object recognition runtime is a major limiting factor in computer vulnerability discovery programs. LAVA a system that can inject vision because the tasks are so complex particularly in real-world bugs in a C program provides a promising technique to easily gen- situations. This project aims to improve object recognition run- erate large corpora of known buggy programs that can be used time and accuracy by inputting salient regions of images — the for evaluation however the bugs that LAVA injects currently suffer most informative parts of the images as determined by humans from a lack of realism. We will focus on improving the realism of or algorithms that approximate human fixations — along with the LAVA bugs by improving their data flow. full images. We will use trained CNNs and enhance them with func- tions that determine and feed in salient regions of input images “A lot of people have tried to research how to discover bugs in and compare our findings with controls. software. My project is essentially to do the opposite: inject real- istic-looking bugs into software at a large scale. Why? Simply put “I am studying both computer science and neuroscience and I’ve being able to easily generate buggy code allows us to evaluate always found a range of topics in math and natural science inter- how effective bug-finding program are at actually spotting errors.” esting. I have had experience applying machine learning to behav- ioral data and now hope to learn more about how my two fields of study interface. This project excites me because it is computer vision a more involved application of my interests.”

Brenda Stern Lawrence Sun MIT CEE — Undergraduate Research MIT EECS Undergraduate Research and Innovation Scholar and Innovation Scholar Project: Life Cycle Carbon Project: Average Case Complexity Emissions for Low-Energy of Statistical Tasks Buildings Advisor: Guy Bresler Advisor: John Ochsendorf I am working with Guy Bresler per- There is a growing emphasis on forming analysis on average case energy efficient design within the structural engineering field, but complexity of statistical tasks.What this means is given a statistical current work focuses on operational energy. Though analysis has task such as performing sparse principle component analysis on shown that embodied carbon can increase as a result of decreasing a data set we use a mix of mathematics and complexity theory operational energy, databases of embodied carbon in structural to provide bounds on various quantities governing algorithms. systems are still being completed. LEED Version 4 now contains For example one bound may be bounding the minimum asymp- a credit for a Whole Building Life Cycle Analysis, which included totic error of an algorithm with polynomial runtime. This is a very embodied carbon, but without complete databases, it is difficult important theory as it can tell us how powerful a given algorithm to have baselines to determine the standing of a new building in is and whether or not it is worth searching for a better algorithm. regard to its embodied carbon. This work will review how LEED determines baseline buildings, contribute to the database by mea- “I decided to participate in the SuperUROP program because suring and benchmarking steel structures, and analyze how LEED’s throughout my years in college I have not had any research expe- results compare against those of the database. rience. Through the Super UROP program I wish to fill this void and learn more about the research process. My project deals with “Previously, I researched in the Concrete Sustainability Hub. a number of fields in mathematics and computer science both I’m excited that this research will let me continue to be of which I enjoy so I look forward to working on this project.” involved in sustainable structural design. In previous architec- ture classes I have taken, the focus was on operational energy usage in buildings, while civil engineering classes focused on concrete as a structural material. This research will help me learn more about the collaboration between the fields.”

2016 – 2017 Scholars 37 Michael Sun Kyle Swanson MIT EECS Undergraduate Research MIT EECS — Angle Undergraduate and Innovation Scholar Research and Innovation Scholar Project: Sparsifying Neural Project: Using Machine Learning Network Connections for DNA and Natural Language Processing Methylation Classification to Detect Cancer Advisor: David K. Gifford Advisor: Regina A. Barzilay

DNA methylation is an epigenetic Despite great advances in cancer state that plays an important role in regulating key biological pro- treatment over the past several decades many forms of cancer cesses such as X-chromosome inactivation, genomic imprinting, especially advanced stage cancer remain resistant to even the and cell differentiation. DNA methylation encodes cellular state strongest doses of radiation and chemotherapy. As a result patient information and changes in methylation levels have been previ- survival often rests largely on early detection via radiological imag- ously reported for cancer and other diseases, but the regulatory ing. Screening patients this way has saved countless lives but suf- mechanism that determines its tissue-specific state is currently fers from inaccuracies even when expert radiologists perform unknown. CpGenie is a deep convolutional neural network that the examinations due to the difficulty of distinguishing between has achieved high performance on predicting allele-specific DNA benign and cancerous abnormalities. The goal of this project is to methylation, but at the cost of a large amount of parameters and improve the accuracy of early detection mechanisms by building low explainability. My project focuses on sparsifying the neural a machine learning model to classify the condition of the patient connections between layers to reduce training time and mem- based on screening images and radiology reports. ory usage by using CpGenie as an autoencoder to train a cascade model. “I first became interested in machine learning when I took 6.036 last spring. I was amazed by the power of the algorithms we “I took part in a research project this summer in machine learning learned so I hoped to explore applications of these algorithms in and became really interested in machine learning research and more depth. Professor Barzilay introduced some of her research its applications to other fields including but not limited to visu- during class and this project sounded like the perfect opportunity alization. This project excites me most because it will give me the to explore my interests while developing a tool that could seriously chance to apply all the skills I have learned this summer to a project benefit patients with cancer.” in a field that I find extremely interesting but also challenging.”

Ertem Tas Erjona Topalli MIT EECS — Landsman MIT EECS — Hewlett Foundation Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: Graphene Sensors and Project: Unconscious Privacy Machine Learning Advisor: Daniel Weitzner Advisor: Tomas A. Palacios Online tracking of users is a major pri- My research project focuses on build- vacy concern in our world today. Cur- ing sensors which measure the effect of the changes in chemical rent approaches consist of blocking all third-party tracking includ- and gas concentration on the device parameters of Graphene elec- ing ads which harms the economy of the Web. Other approaches trolyte-gated field-effect transistors (EGFETs) especially their min- consist of more fine-grained tools that give the user information imal conduction (Dirac) point. Hence I will design analog circuits about the trackers and the control of allowing them or not. In this to facilitate tracking of the Dirac point through feedback mecha- paper we propose a novel alternative. While the latter solution nisms. Afterwards I will work on fabrication of these sensors and gives the user some agency it does not give the user full infor- increasing their selectivity through machine learning algorithms. mation on the data that is actually being aggregated. We hope to Finally this project aims to extend the application of EGFETs to build a system that tracks the trackers but gives the user a simple cover areas such as smart-skin technology and novel large-scale and understandable visualization of the data tracked by different integrated systems. users.

“I believe that the SuperUROP program will not only equip me “I am very interested in privacy and whole realm of security. I want with skills crucial to success in graduate academic research but to research and bring more attention to ways in which users are also increase my knowledge in circuits and their applications in endangered.” material physics areas which attract my attention. In this context classes I took in MIT skills I brought from my summer internship focused on circuit design and my physics olympiad past prepared me for the research.”

38 2016– 2017 Scholars Samir Wadhwania Madeleine Waller MIT AeroAstro — Northrup Undergraduate Research and Grumman Undergraduate Research Innovation Scholar and Innovation Scholar Project: Verification Testing of Project: Designing and DHU Firmware for TESS Implementing Geometric Advisor: George Ricker Reasoning Solvers for RMPL Planners with a PMT Approach For my SuperUROP project I will be Advisor: Brian Williams working with the MIT Kavli Institute on the development of a Transiting Exoplanet Survey Satellite I propose to design a PMT-based language for geometric reasoning (TESS) scheduled to be launched in 2017. TESS’s purpose is to in RMPL to be integrated in path planning algorithms for an Auton- identify small planets in the solar neighborhood and to perform omous Underwater Vehicle. Employing the formal techniques of detailed characterizations of the planets and their atmospheres. I PMT will require developing core and module files for the solver will be assisting with the hardware component of TESS working investigating the effectiveness of automatic heuristic generation with the FPGAs on board the satellite to incorporate rate checking with a geometric reasoning-based domain and implementing the and error insertion testing into the design for verification purposes. solver that an RMPL planner will call. Exploring the development of one PMT-based solver will hopefully lead the way breaking down “I’m a senior studying electrical engineering and computer science all solvers into core and module files to be used by the planner. and I’ll be working with the TESS team in the MIT Kavli Institute. I Successful implementation of the geometric reasoning solver will joined the lab last spring after taking 6.111: Intro to Digital Sys- allow for the eventual transition of the planner and sub-solvers to tems Laboratory and learning how to work with FPGAs. I chose to one that fully implement formal Planning Modulo Theories. pursue a SuperUROP project because I enjoyed my work last spring and it sounded like a great opportunity to get further involved in “I am an upcoming junior studying courses 16 and 6-2. I am per- research.” sonally interested in the domains of Autonomous Systems Robot- ics and Space Exploration. I’m excited to work on this SuperUROP because of its applications to many different types of rovers space- craft and autonomous vehicles. I hope to gain experience with AI with respect to robotics and plan to use what I learn to continue working in space exploration!”

Andy Wang Li Wang MIT EECS Undergraduate Research MIT EECS Undergraduate Research and Innovation Scholar and Innovation Scholar Project: Automatic Tools for 2-D Project: Understanding the Animation Ambiance of Images: Emotional Advisor: Justin Solomon Visual AI Advisor: Dorothy W. Curtis This project explores algorithms and software for 2-D animation that make This project focuses on creating a the motion between keyframes more natural. It is aimed at sim- system that can identify psychological effects of images and envi- plifying the process of animation primarily to help amateur ani- ronments to passively ameliorate the human state of mind in vary- mators more easily produce and control the “squash” and “stretch” ing surroundings. Psychologist have theorized that people have motions typical of classic animated characters. In a more detailed adapted to have inclinations towards scenes of nature or animals description the problem that the project aims to solve is planar because living in such environments as a pre-historic human shape interpolation where given the start and end frame of an ani- meant survival and successful reproduction. These adaptations mation we need to produce the frames in between in order to occurred before the formations of societies and cultures and are produce a continuous and natural looking motion. Current meth- considered to be independent a person’s race or personal past. A ods in industry can be time-consuming and we make a design wide selection of training data from humans will be collected and decision to trade off some degree of generalizability to general used to train the system. We will then evaluate its performance structures for time and simplicity and smooth animations. against the analysis of images by human subjects.

“My main goal is to learn about the existing technologies that exist “I am studying both computer science and neuroscience and I’ve in the field of animation both 2-D and 3-D (although the project always found a range of topics in math and natural science inter- entails animation within the 2-D space). In addition one of the best esting. I have had experience applying machine learning to behav- ways to learn and understand a concept is to try to implement. So I ioral data and now hope to learn more about how my two fields believe that undertaking this project will allow me the opportunity of study interface. This project excites me because it is computer to implement it in an encouraging environment under the guid- vision a more involved application of my interests.” ance of Professor Solomon.”

2016 – 2017 Scholars 39 Mark Wang Mike Wang MIT EECS — Lal Undergraduate MIT EECS Undergraduate Research Research and Innovation Scholar and Innovation Scholar Project: Analysis of Flash Crashes Project: Analyzing Medical Data in Economic Data Advisor: Dorothy W. Curtis Advisor: Alan Edelman Several sensors had been deployed The purpose of the research proj- earlier on wheelchair of people with ect is to analyze a large database of multiple sclerosis and these sensors the New York stock exchange data (with a size of 14.5 terabytes) have picked up more than 260 hours of data about the patients in order to detect financial irregularities. Of particular interest is and the ambient environment. My project is to work on analyzing a “flash crash” a phenomenon in which there is a very deep and the data to find statistics about the patients and trends in their vital volatile fall in stock prices within an extremely short period of signs data (for example find the frequency patients go outside). time. These crashes can be evidence of quasi-legal trading prac- Specific responsibilities I have for the project includes developing tices such as quote stuffing or spoofing. The project will focus algorithms to detect when a specific event occurs analyzing the on developing and implementing a program which can detect data to find when and at what frequency the event occurs and these extreme fluctuations in order to determine how common giving general summary statistics about the patients. flash crashes are as well as to determine if there are correlations between flash crashes. “I am going to be a junior majoring in computer science and math- ematics. The superUROP project is going to be about data analy- “My name is Mark and I am a computer science major. I am sis and I hope to learn more about different methods to analyze prepared for the research by the classes I have taken at MIT data and become comfortable doing it. This project is exciting not as well as an UROP research project at the Julia Lab. Through only because it is a great exercise to learn but also because it is the UROP I got acquainted with the lab and with large data for a good cause (helping to understand multiple sclerosis and its sets. I hope to learn about clever ways to mine a data set. patients).” What I find exciting about the project is its flexibility and inde- pendence as well as a change to deal with so much data.”

Zhishen Wang Brian Wheatman MIT AeroAstro — Lincoln Laboratory MIT EECS — Lockheed Martin Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: Optimizing Padding on Project: Tourist Path Optimization Inverted Helmet Design Problem Advisor: Raul Radovitzky Advisor: Sertac Karaman

Sports related concussions occur We wish to study a variant of the Prize often in high school sports and can be detrimental to the adoles- Collecting Traveling Salesmen Problem. Specifically given a set of cent brain. Current football helmet designs protect against impact nodes each with a time dependent reward function and a set and concussions but could use improvement in design. Tradi- edges each of which has a cost in time to travel return a path that tional helmets have a hard shell on the outside and a soft cushion- maximizes the total reward given a total time and returns to the ing layer on the inside. One redesign of the football helmet is the start. The Dual of minimizing the time required to achieve certain inverted helmet concept. Previous research has shown that plac- level of reward is also of interest. What is unique about this prob- ing the cushioning layer on the outside may have better results lem is that the reward for going to a node is dependent on the to prevent concussions. My research focuses on determining the amount of time you spend at each node and thus the optimization optimal foam to use for the inverted football helmet design. Tests must be done not only over which nodes to visit but also how long will be performed on foam samples in a drop tower to simulate to stay at each node for. The goals for this project are to develop an impact. The results will be analyzed to find the best shock absorb- Online or Approximation Algorithm to allow us to compute good ing foam for this application. solutions efficiently.

“The SuperUROP program provides me a chance to conduct my “I am a senior studying computer science and math. I am looking own guided research and gives me access to many resources. forward to this project to leverage my experience in both of these I hope to gain more research experience and ultimately work fields to approach a basic problem with many higher level appli- towards a safer helmet design.” cations. Throughout the year I hope to gain insights into how to develop new algorithms and how to modify existing ones to solve new problems.”

40 2016– 2017 Scholars Sze Nga Wong Jimmy Wu MIT EECS Undergraduate Research MIT EECS — Angle Undergraduate and Innovation Scholar Research and Innovation Scholar Project: Development of Neural Project: Object Detection for Architectures for Improving Robotic Systems Machine Translation Advisor: Antonio Torralba Advisor: Tommi S. Jaakkola Our goal for this project is to develop With the advance of communication an object detection system for technologies, machine translation serves as a scalable tool for robotic systems using computer vision techniques. Robotic sys- people to acquire knowledge represented in different languages. tems use object recognition systems to build maps of their envi- Improving machine translation accuracy is an urgent matter. This ronment which are subsequently used in various aspects of auton- can be achieved with suitable embeddings that resemble seman- omous control such as path planning and localization. We plan to tic relatedness. I aim to build a neural architecture for training bilin- apply a full scene segmentation approach to do object detection. gual phrase embeddings in an end-to-end fashion, using data from As applied to object detection image segmentation allows the existing linguistic databases. The architecture will involve building robot to recognize objects of interest in the input visual feed and bilingual word embeddings using curriculum training, and train- pinpoint the exact pixel locations of these objects. An autonomous ing the bilingual phrase embeddings by the BRAE model. robot navigating indoors would for example be able to perform segmentation on its camera feed to determine pixels of the image “My project is on neural machine translation. I have taken classes corresponding to the ground walls and other obstacles such as in statistics and algebra which give me a solid mathematics back- tables and chairs. ground to understand the theoretical concepts in natural lan- guage processing. Neural networks have been proved useful in “I became interested in robotics and computer vision while taking many areas including NLP and I believe it has a greater power yet 6.141 and doing research with Prof. Torralba’s group last spring to be discovered. I hope to learn about the state-of-the-art theo- and have worked on machine learning and deep learning projects ries in the field and their applications.” at previous internships. I hope to get some meaningful research experience through the SuperUROP program.”

Raymond Wu Andrew Xia MIT EECS Undergraduate Research MIT EECS — MITRE Undergraduate and Innovation Scholar Research and Innovation Scholar Project: Optimizing Simit: A Project: Leakage Resistant Public language for physical simulations Key Authentication for Embedded Advisor: Saman P. Amarasinghe Devices Advisor: Anantha P. Chandrakasan This project will focus on Simit which is a language for physical simulations. This SuperUROP project will aim Many current systems that deal with physical simulations such as to implement a working version of a leakage resilient public key Matlab currently use linear algebra to describe the behavior of the encryption scheme for embedded applications in which the pri- physical system. However there are significant performance costs vate key will update on every iteration of the authentication proto- for the programmer and the machine when translating between col while the public key stays fixed to prevent side channel attacks. linked data structures and matrices. Simit’s design allows it to be This platform will allow for effective authentication communica- the first language for physical simulations that is concise expres- tion between embedded systems. sive fast performance portable and interoperable. The language allows programmers to write code at a high level and get per- “I am participating in the SuperUROP program because I am very formance of optimized low-level code. Some further research to interested in applying my microcontrollers knowledge (from 6.115) improve Simit’s performance can be accomplished with certain and mathematics background to a longer term research project compiler optimizations and transformations. and also gain a better understanding of cryptography. I hope to further my knowledge in crpytography programming and also “I have taken 6.172 and 6.035. I hope to gain a greater understand- learn about how to work on a successful research project.” ing of compilers and optimizing them. I’m excited for the many challenges that the project will bring.”

2016 – 2017 Scholars 41 Mengjiao Yang Rachel Yang MIT EECS — Slaughter MIT EECS — Analog Devices Undergraduate Research and Undergraduate Research and Innovation Scholar Innovation Scholar Project: Scalable Web Project: High-Frequency Power Development with Event-driven Magnetics with Multi-Material Programming and Actors Cores Advisor: Daniel N. Jackson Advisor: David J. Perreault

Developing a scalable web application requires additional effort Operation in the HF regime (3-30 MHz) has shown promise in to manage multiple aspects of the web application such as cli- achieving miniaturization of power electronics. Power magnetic ent-server communication real-time data fetching and tech- components, which are often the largest parts of these circuits, niques needed for scaling. The traditional Model View Controller have greater performance factor at high frequencies, demon- (MVC) design model often times has problems meeting the robust- strating the potential for miniaturization. Winding loss, however, ness and efficiency desired by scalable web applications. The goal becomes a large limiting factor in reducing the size of these com- of this project is to construct a event-driven programming model ponents at HF. The proposed approach for minimizing this loss is for building applications that frees developers from the complex- to reduce ac winding resistance with multi-material cores. To do ity of distributed computing and provides separate ways to control so, performance optimization methods for different multi-material performance and scalability. This project will extend the existing core geometries, such as the dumbbell geometry, will be devel- event-driven model to support actor model of concurrent com- oped. In this way, reduced winding loss may be achieved in these putation which essentially uses message passing techniques to power magnetic components, allowing for successful high-fre- achieve the level of concurrency. quency operation and thus, miniaturization.

“I am interested in distributed programming and have taken the “I really enjoyed my UROP with the Power Electronics Research computer systems class. I also touched on web backend and frame- Group last semester and wanted to get even more hands-on work implementations during my past internships. This project will EE experience. I’m also excited to delve into some interesting be a valuable experience for me to apply what I’ve learned from magnetics by investigating properties of multi-material cores.” the classroom to developing real-world applications and poten- tially affecting how such systems are programmed.”

Rujie Yao Elisa Young MIT EECS — Angle Undergraduate MIT EECS — Keel Foundation Research and Innovation Scholar Undergraduate Research and Project: Continuous Perfusion Innovation Scholar Culture Using Novel Microfluidic Project: Lighting Estimation in Separation Devices Augmented Reality Advisor: Jongyoon Han Advisor: Frederic P. Durand

Biopharmaceutical drugs are com- In augmented reality (AR) it is often monly produced through mammalian cell culture and perfusion desirable for virtual objects to be blended into their real world sur- culture is often used for its high levels of cell concentration and roundings indistinguishable from real objects to the user. How- productivity. However, current cell retention devices based on ever current AR setups face many challenges and virtual objects membrane filtration can lead to fouling and clogging of the mem- are often displayed with static lighting rather than adjusting to brane during long-term perfusion culture. The goal of my project the environment’s actual lighting conditions. For this project we is to investigate the use of a newly developed cell retention device will infer lighting conditions from the environment to allow 3-D in perfusion culture. This membrane-less microfluidic device uses objects to be realistically represented in AR in real time. In a larger size-based inertial sorting to continuously separate viable and context this contributes to computer vision and graphics tech- non-viable cells. It does not suffer from fouling and clogging and niques useful to autonomous vehicles for inferring information thus is ideal for long-term applications in cell culture. Possible ben- about the environment as well as many other emerging technol- efits include enhanced antibody productivity and cell viability. ogies outside of AR.

“I learned about lab techniques and cell biology during lectures “I found the computational photography and computer graphics but I wanted to be able to apply what I’d learned to outside of the courses fascinating and am now exploring these subjects further classroom. I’m excited for this opportunity to work at the inter- through SuperUROP. Getting to contribute research in these fields face of engineering and the life sciences on a project that could especially in the context of augmented reality for my project is really make a difference in the biopharmaceutical industry. I hope quite exciting.” to learn more about microfluidics and their various applications along the way.”

42 2016– 2017 Scholars Chengkai Zhang Jessie Zhao MIT EECS — Analog Devices MIT ChemE — Undergraduate Undergraduate Research and Research and Innovation Scholarr Innovation Scholar Project: Addressing Determinants Project: One-shot learning for of Antibody Specificity vision-as-inverse graphics Advisor: Karl Dane Wittrup Advisor: William T. Freeman As in vitro immune repertoires Reconstructing and retrieving 3-D derived from display systems have shapes from 2-D images has long been a focus in computer vision. grown increasingly popular as an alternative method to isolating It is a challenging problem because of the ambiguity in 3-D to 2-D antibodies there is greater need for improved screening methods projection. In this project we plan to tackle this problem by adopt- to select for antibodies that have favorable developability profiles ing the recent advance in deep convolutional generative adversar- and select against antibodies that show signs of aggregation poor ial network (DCGAN) and aim to generate 3-D shape from vectors. stability and nonspecificity. This project aims to develop an ear- We also plan to train a convolutional neural network that maps an ly-stage platform combining yeast surface display and antibody image to a vector accordingly. To further improve performance we library design that can detect and correlate upstream nonspecific- plan to explore different constraints during network training to ity to downstream developability of antibodies in order to improve encode object continuity physical stability and contour consis- the late-stage success of monoclonal antibody therapeutics devel- tency. oped from display platforms.

“I took a graduate level machine learning class in the fall of my “Through SuperUROP I intend to explore protein engineering and junior year and then started UROPs in the field of computer vision biotherapeutic design in understanding antibody nonspecificity.” and deep learning. One of my UROPs studied the stability of pile of blocks in images and another studied the use of DCGAN network on 3D objects. The most exciting part of this project is the oppor- tunity of combining these experiences and building a high-perfor- mance object retrieval model.”

Helen Zhou Hugo Zul Undergraduate Research and MIT EECS — Hewlett Foundation Innovation Scholar Undergraduate Research and Project: Predicting Food Purchase Innovation Scholar Behavior Using Multimodal Deep Project: Machine Learning and Neural Networks CyberSecurity in Software Defined Advisor: Deb Roy Networks Advisor: Una-May O’Reilly My project aims to predict food pur- chase behavior by combining information from multiple modal- The flexibility of Software Defined Networks has resulted in ities (such as tweets news weather census data and product increasing growth and adaptation. However recently alarming descriptions). Multimodal learning is a relatively new machine hacking vulnerabilities have been revealed. The project will involve learning technique and has been shown to improve over per- applying machine learning to replicate how topology poisoning formance with just one modality. By training deep Boltzmann can be used for eavesdropping and how to detect the fake links machines on two distinct modes and then combining these into a introduced into the network by the attacker. shared feature representation we will have a more robust input for our deep neural network. “It should be mandatory that you understand computer science.” — will.i.am “Throughout my years at MIT I’ve found machine learning and computer vision highly interesting and I’m excited to dive into exploring this new direction that combines information from a variety of channels. I hope to deepen my understanding of state- of-the-art machine learning techniques as well as develop my research skills.”

2016 – 2017 Scholars 43 SuperUROP is made possible by the generous support of the following donors and industrial sponsors.

Alumni and Friends Industrial Sponsors Erika N. ‘04 and Colin M. Angle ‘89, SM ‘91 Analog Devices, Inc. Robert M. Fano ‘41, ScD ‘47 Boeing Renée and Steven G. Finn ‘68, SM ‘69, EE ‘70, ScD ‘75 Cisco Hewlett Foundation Draper Hudson River Trading Lincoln Laboratory Keel Foundation Lockheed Martin Sheila E. and Emanuel E. Landsman ‘58, SM ‘59, ScD ‘66 MITRE R. Franklin Quick, Jr. ‘70, SM ‘70 Northrop Grumman Dinarte R. Morais ‘86 and Paul Rosenblum, Jr. ‘86 UTC-Pratt & Whitney Mimi I. ‘87, SM ‘88 and Frank G. Slaughter ‘84 Seven Bridges Genomics

Texas Instruments

Below: Electrical engineering and computer science Opposite page: Chemical Engineering junior Marjorie senior Daniel Richman is working on a project aimed Buss is working on a project engineering the biosyn- at creating more secure wearables and embed- thesis of coenzyme M in E.coli, a step toward devel- ded devices for the Internet of Things. Richman is oping methods for the bacteria to convert harmful developing new communications protocols using substances into useful chemicals like biofuels. in-packet frequency hopping to stop jammers and minimize power consumption.

44 Industrial Sponsors

“Boeing is proud to sponsor MIT’s AeroAstro SuperUROP because the program helps prepare students to be strong contributors in the aerospace field by strengthening their advanced-research ca- pabilities, business acumen, communication skills, and knowledge of our industry.” — John Tracy Chief Technology Officer, Senior Vice President, Engineering, Operations & Technology, The Boeing Company

“The SuperUROP program brings students and faculty togeth- er to work on a year-long independent research project. It’s a great opportunity for students to take the lead on a project that they care deeply about, and to see it through to a mean- ingful conclusion.”

—Dennis Freeman Dean for Undergraduate Education Professor of Electrical Engineering MacVicar Faculty Fellow

45 EECS Department Head Anantha P. Chandrakasan Office of Philanthropic Partnerships acknowledges the following contributors to the 2016–2017 John Currier, Philanthropic Advisor SuperUROP program. Office of Campaign Planning Office of the Dean for Undergraduate Education Sharon Stanczak, Senior Associate Director Dennis M. Freeman, Professor, MacVicar Fellow, Dean for Brad Smith, Director of Strategic Initiatives — MIT.nano Undergraduate Education School of Engineering Julie B. Norman, Senior Associate Dean for Undergraduate Ian Waitz, Dean of Engineering Education, Director, Undergraduate Advising and Academic Danielle R. Festino, Assistant Dean for Development Programming Chad Galts, Director of Communication Michael Bergren, Associate Dean, Academic and Research Tia Giurleo, Manager of Development Services and Special Initiatives, Undergraduate Advising & Academic Programming Projects J. Alex Hoyt, Administrative Assistant Mary Markel Murphy, Assistant Dean for Human Resources and Administration Office of the President Meg Murphy, Staff Writer L. Rafael Reif, MIT President Lillie Paquette, Multimedia Producer Israel Ruiz, Executive Vice President and Treasurer Lesley Rock, Development Communications Officer Aaron R. Weinberger, Assistant Director for Institute Affairs Michael Rutter, Director of Media Relations

Office of the Chancellor MIT EECS Cynthia Barnhart, MIT Chancellor Neerja Aggarwal, 6.UAR Teaching Assistant, Fall 2016 Dorothy Curtis, Research Scientist, CSAIL, EECS Data Officer Office of the Recording Secretary Ted Equi, EECS SuperUROP Industrial Liaison Elizabeth Ogar, Recording Secretary and Executive Director Elaheh Fetah, 6.UAR Teaching Assistant, Fall 2016 of Administration Myron Freeman, Manager of Departmental Computing Linda Mar, Associate Director, Fund and Campaign Recording Dina Katabi, Andrew (1956) and Erna Viterbi Professor Kathy D. Vitale, Senior Associate Recording Secretary Veronica Lane, 6.UAR Teaching Assistant, Fall 2016 Maureen Moran, Gift Operations Manager Yuri Polyanskiy, Robert J Shillman (1974) CD Assistant Professor of Electrical Engineering and Computer Science Office of Leadership Giving Audrey Resutek, Communications Officer Elizabeth Barbuto, Individual Giving Officer Lindsay Shanahan, Administrative Assistant Kate Boison, Leadership Giving Officer Jarina Shrestha, Fiscal Officer Brian R. Kern, Senior Leadership Giving Officer Mary Ellen Sinkus, Administrative Officer Nancy O’Brien, Leadership Giving Officer Srinidhi Viswanathan, 6.UAR Teaching Assistant, Fall 2016 Kathleen Vieweg, Leadership Giving Officer Electrical Engineering and Computer Science junior Amir Karamlou adjusts an optics setup in the Quantum Photonics Lab. Karam- lou is working on a project aimed at enhancing spin readouts in nitrogen vacancy qubits, an important measurement for quantum information processing.

46 MIT AeroAstro Jaime Peraire, Department Head, H.N. Slater Professor of Aeronautics and Astronautics Joyce Light, Program and Strategic Initiatives Coordinator William Litant, Communications Director

MIT Biological Engineering Douglas Lauffenburger, Department Head, Ford Professor of Engineering Eric Alm, Associate Professor of Biological Engineering Diana Chien, Graduate Student, Communications Lab Fellow Thomas Gurry, Postdoctoral Researcher

MIT Civil and Environmental Engineering Markus J. Buehler, Department Head, McAfee Professor of Engineering Ruben Juanes, Associate Professor of Civil and Environmental “Texas Instruments has been passionate about creating Engineering Stephanie Bright, Academic Administrator innovative technology solutions for more than 80

MIT Chemical Engineering years. I believe our industrial sponsorship of the Supe- Paula T. Hammond, Department Head, David H. Koch Professor rUROP program is a vital investment in our future. We in Engineering Barry Johnston, Undergraduate Officer are excited to partner with MIT students and faculty

MIT Nuclear Science and Engineering to pioneer new research projects and to successfully Dennis Whyte, Department Head, Professor of Nuclear Science push boundaries and explore new horizons together.” and Engineering Richard Lester, Associate Provost for International Affairs, — Rich Templeton Professor of Nuclear Science and Engineering Chairman, President and Chief Executive Officer, Michael Short, Assistant Professor of Nuclear Science and Texas Instruments Engineering Clare Marie Egan, Graduate Office Administrator

Chemical engineering senior Minsoo Khang is working on a project in Prof. Robert Langer’s lab aimed developing an oral drug delivery device for insulin.

47 Left: Ignacio Estay Forno, a junior “MIT Lincoln Laboratory strives to develop studying electrical engineering, adjusts a sputtering system in the innovative technical solutions for very diffi- Quantum Nanostructures and Nanofabrication Lab. Estay Forno cult national security problems. The Super- is working on a SuperUROP proj- UROP program has been a great way for us to ect in Prof. Karl K. Berggren’s lab aimed at developing a method to strengthen our relationship with outstanding interface with nanoscale single photon detector arrays. MIT students and faculty and to find very cre- ative new ideas for advancing the programs we have. We have really benefitted by being involved.” — Eric Evans Director, MIT Lincoln Laboratory

“As an industrial sponsor, Analog Devices will look for opportunities to collaborate with students and faculty on research topics of continual interest and provide insights into the relevance of research to real world applications. Analog Devices is excited about exploring new possibilities to strengthen our relationship with MIT students and faculty through the SuperUROP program.”

— Raymond S. Stata ‘57, SM ‘58 Chairman and Co-Founder, Analog Devices Inc.

48 Cover Photos Top row Chemical Engineering junior Marjorie Buss is working on a project engi- neering the biosynthesis of coenzyme M in E.coli, a step toward developing methods for the bacteria to convert harmful substances into useful chemicals like biofuels. Middle row, left to right Electrical engineering junior Ignacio Estay Forno prepares a silicon nitride substrate for thin film deposition. Electrical Engineering and Computer Science senior Ebenezer Nkwate per- forms restriction digestion. Nkwate is working on a project to build genetic logic gates that target and proliferate heart cells. Bottom row AeroAstro major Rachel Morgan (photo by William Litant) is working with advisor Kerri Cahoy on a nanosatellite lasercom system. Electrical Engineering and Computer Science junior Amir Karamlou has been working as a UROP in the Quantum Photonics Lab since he was a freshman. He is now working with Prof. Dirk Englund on a SuperUROP project aimed at improving the readout of qubits in nitrogen vacancy centers in diamonds, an important measurement in quantum information processing. “SuperUROP provides a tremen- Chemical engineering senior Minsoo Khang is working on a project in Prof. dous opportunity for MIT’s Robert Langer’s lab aimed developing an oral drug delivery device for insulin. engineering students to gain All photos in brochure are by Gretchen Ertl unless otherwise noted. meaningful research experi- Research Guide designed by Audrey Resutek ence in world-class labs. I have been delighted to observe the program’s impact in shaping how our students understand the role research plays in ad- dressing important challenges.” “SuperUROP in its design is so quint- — L. Rafael Reif essentially MIT, particularly because it President, MIT builds on MIT’s tradition of mens et ma- nus, and it is aligned with the Institute’s priorities of discovery, innovation, and making the world a better place.”

— Cynthia Barnhart Chancellor Ford Professor of Engineering

49 SuperUROP, launched in 2012, is an expanded version of Department of Aeronautics and Astronautics MIT’s Undergraduate Research Opportunities Program Department of Biological Engineering (UROP). The year-long program gives juniors and seniors Department of Civil and Environmental Engineering the opportunity to conduct publication-worthy research, Department of Chemical Engineering and provides a primer on issues surrounding modern Department of Electrical Engineering and Computer Science research. SuperUROP is hosted by the Department of Department of Nuclear Science and Engineering Electrical Engineering and Computer Science, with students in the following departments in MIT’s School of Engineering: Photo: 2015-2016 SuperUROP class. Photo by Gretchen Ertl

http://superurop.mit.edu