• Massachusetts Institute of Technology, Class of 2012, PhD in Computer Science (GPA: 5.0/5.0)
• Cambridge University, Class of 2009, M.Sc. in Engineering
• Massachusetts Institute of Technology, Class of 2007, M.S. in Computer Science (GPA: 5.0/5.0)
• Massachusetts Institute of Technology, Class of 2005, B.S. in Aerospace Engineering, B.S. in Physics, Minor in Creative Writing, (GPA: 5.0/5.0)
• Governor’s School for Government and International Studies, Class of 2001 (GPA: 4.0/4.0)

My core research interest lies in developing unsupervised machine learning techniques that have both high predictive and explanatory power. My current projects include understanding the temporal evolution of Autism Spectrum Disorder and evaluating drug efficacy among diabetics using electronic health records (EHRs). While EHRs provide an inexpensive way to look at large clinical populations, they are extremely sparse and incomplete. Specifically, I am interested in models and inference procedures that can take advantage of input and intutions from experts in a flexible and robust manner.

More generally, I am interested in a variety of machine learning problems centered around Bayesian modeling and sequential decision-making. My doctoral work focused on applying Bayesian nonparametrics to reinforcement learning problems in partially observable domains. For my first masters, I developed an adaptable dialog manager for a robotic wheelchair using a planning paradigm known as partially observable Markov decision processes. During my second masters, I worked on efficient inference techniques for scaling Bayesian non-parametrics to large, real-world problems. In particular, I developed efficient inference algorithms for a latent feature model known as the Indian Buffet Process, which has applications ranging from detecting software bugs to modeling protein interactions.

• Research Associate in Bioinformatics, Harvard Medical School Center for Biomedical Informatics, September 2012 - Present. Applying Bayesian techniques to cluster and make predictions from clinical data; projects include predicting seizures among autism patients and characterizing cardiovascular risk among healthy women (continuing projects from BWH).
• Fellow, Harvard School of Engineering and Applied Sciences, January 2012 - Present. Applying Bayesian nonparametric techniques to reinforcement learning domains and developing novel Bayesian nonparametric models.
• PhD Thesis: Bayesian Nonparametric Methods for Reinforcement Learning in Partially Observable Domains, MIT Fall 2009-Spring 2012. Bayesian Nonparametric Methods are well-suited to reinforcement learning problems where the size of the world is unknown and new areas may be explored over time. My work involved designing Bayesian nonparametric models suitable for reinforcement learning problems and developing the inference techniques to apply them to interestingly-sized domains.
• Master's Thesis: Indian Buffet Process: Efficient Inference and Extensions, Cambridge Fall 2007-Summer 2009. The Indian Buffet Process is a nonparametric prior of modeling hidden factors in data. My work developed efficient inference techniques for working with this model.
• Master's Thesis: POMDPs for Dialog Management, MIT Fall 2005-Summer 2007. POMDPs are powerful tools but in the dialog management domain, the model parameters are often poorly specified or unknown. My work combined online parameter learning with prior beliefs over the POMDP parameters.
• Junior-Senior Design Project, Design for a radiator-cooling cascade. Junior-senior design partner project to design an airfoil-based radiator cascade for cooling air from a turbine. Winner of annual manufacturing award.
• Undergraduate Research Project, Video Matching, MIT Spring 2005. Worked with a graduate student to improve video alignment techniques for robot localization.
• Undergraduate Research Project, Vision-based Gesture Recognition, MIT Fall 2004 – Spring 2005. Self-directed project to create and integrate a gesture recognition interface on an existing robot to aid the elderly.
• Research Associate, 2004 NASA Academy, NASA Goddard. Developed and implemented algrorithms for minimum-fuel spacecraft rendezvous. Goddard Research Award recepient.
• Undergraduate Research Project, Model-based Embedded and Robotic Systems Group, MIT, Fall 2003. Tested fault-detection and correction software for autonomous rovers.
• Undergraduate Research Project, Alternative Keyboard Project, Spring 2002 – Summer 2003. Self-directed project under the MIT Edgerton Center; designed and built a key input device for people with wrist injuries.
• Spacecraft Control research assistant, Space Systems Lab (MIT), Cambridge MA, Winter 2002. Built the control circuitry for testing a flywheel design.

• Instructor, Statistics for Research Projects, MIT Winter 2010-2012 (EECS); Winter 2011 (EECS); Summer 2011 (Sloan PhD Programl). Developed curriculum for and taught a 6-unit course on practical statistics for graduate and undergraduate researchers. Received a teaching quality rating of 6.3/7, where 6 is “excellent” and 7 is “best.”
• Supervisor (tutor), Cambridge University, Fall 2007, Fall 2008, Winter 2008. Provided small group and individual tutoring for third-year signals and systems and fourth-year statistical modeling.
• Program Director, Maslab Robotics Contest, MIT, Fall 2004 – Spring 2006. Directed a completely student-run autonomous vision-based navigation robotics contest. Duties included organizing the production of student kits (involved $25K of fundraising), designing curriculum, and managing a 10-person teaching staff/lab schedules as well as teaching and other interactions with the students (also 2003 participant, 2007 staff).
• Teaching Assistant, MIT Spring 2007. Presented recitations for a graduate course on inference and information. Rated as 6.3/7 in course evaluations from 11 responses, evaluation summary read: “was highly praised as an amazing TA. Students complemented her knowledge of the field, great blackboard techniques, and clear explanations. All 9 comments were positive.”
• Instructor, MIT Fall 2005, 2006. Independently taught sections of freshman single and multivariable calculus.
• Teaching Assistant, MIT Spring 2002 – Fall 2006. Presented tutorials for freshman physics, single and multivariable calculus, and differential equations; winner of the Todd Anderson teaching award.

• Project Mentor, Winter 2013—Present. Massachusetts Institute of Technology. Supervised two undergraduate students to apply basic machine learning techniques to predict diagnoses in autism spectrum disorders and inflammatory bowel disease.
• Bachelors Thesis Mentor, Winter 2012—present, Wellesley College. Co-supervised two undergraduate theses to predict energies of solvation based on molecular features.
• Project Mentor, Fall 2012-Spring 2013. Harvard. Supervised a project to classify pot-holes based on smart phone accelerometer data.
• Project Mentor, HMS Summer 2012. Supervised an undergraduate project looking at pathways with high differential gene expression between autistic individuals and a healthy population.
• Project Mentor, MIT Summer 2010. Helped supervised an undergraduate project for localizing wheelchairs using wifi signal strengths.
• Masters thesis mentor, Cambridge University, Fall 2008 - Spring 2009. Helped supervise a fourth-year project in determining the structure of Bayesian networks with large amounts of missing data with application to water and sanitation.
• Junior-Senior Project Mentor, MIT Spring 2007. Helped supervise a junior-senior project in the effectiveness of wheelchair dialog managers.

• Bioinformatics Analyst, Brigham and Women's Hospital, April 2012 - August 2012. Applying Bayesian techniques to cluster and make predictions from clinical data; projects include predicting seizures among autism patients and characterizing cardiovascular risk among healthy women. Research Fellow, September 2012 - Present.
• Intern, ITA Software, Summer 2007. Applied machine learning techniques for econometric analysis of flight data.
• Lab Assistant, Sentor Technologies Inc., Richmond VA, Summer 2003. Programmed and built control circuitry for a contactless gamma ray detector, built reels for electrospray applications.

• Co-organizer, NIPS Workshop 2013 on Machine Learning for Clinical Data Analysis.
• Co-organizer, ICML Workshop 2011 on Decision-Making with Uncertain Models. Duties included seeking invited speakers, program-chairing, and publicity.
• Co-organizer, AAAI Spring Symposium 2011 on Computational Physiology. Duties included seeking invited speakers, program-chairing, and publicity.
• Workshop for Women in Machine Learning: Co-organizer (2009), co-founder and interim co-chair of the Executive Board (2010), member of the Executive Board (2010-2012), President of the executive Board (2013-present). Workshop organizing duties included fundraising (about $25K), program-chairing, and publicity. Board duties included building procedures for sustaining the workshop, as well as writing NSF grants for multi-year workshop funding.
• Program Chair, Interdisciplinary Graduate Conference, Cambridge, 2009. Organized submission and review process for abstract submissions, as well as aided with other conference logistics and scheduling.
• Reviewer for the following journals: Autonomous Robots, Autonomous Agents, Autonomous Agents and Multiagent Systems; and conferences: AAAI 2008, RSS 2011, IROS 2011, NIPS 2009-2012, AISTATS 2010-2013, ICML 2010-2013.

• Committee on Foreign Scholarships, member 2009-Present (mentored MIT students applying for foreign scholarships, participated in mock interviews)
• REF, EECS Department, MIT Summer 2010-Spring 2012. Peer mediator, conflict coach, and stress reduction resource for graduate students. Certification includes 32 hours of mediation training. Our organization was nominated for the Compton Award, the Institute's highest honor for excellent achievements in citizenship and devotion to welfare of MIT.
• Academic Chair, EECS Graduate Student Association, MIT Spring 2010. Introduced new research buddies program to partner students with similar research across different labs, helped organize other academic preparation events.
• Organizer and founder, Robotics Tea, MIT Robust Robotics Group Summer 2010-Fall 2010. Started a weekly robotics tea for lab members to present summaries of interesting papers and catch up with others.
• Co-founder, Executive Committee Member; Graduate Students at the Cambridge University Engineering Department, Spring 2007. Founded a student organization to liaise with the department administration, organize events for sharing research (including a poster session in Fall 2008), and hold various social networking events.
• Social Chair, Machine Learning Group, Cambridge Fall 2007-2009. Organized fun (pi day celebration) and educational activities (such as one-day seminar on reinforcement learning) for the group. Also organized a research buddies program for students to discuss work with each other.
• Program Chair, CSAIL Student Workshop, MIT EECS, Fall 2007. Organized review process for student paper submissions and best paper awards. Subsequently won Best Paper Award in 2010.
• Discussion Coordinator, MIT EECS, Summer 2007. Organized a series of roundtable discussions on graduate student life, culminating in a concrete set of suggestions to the department for improvement.
• Orientation Co-chair, MIT EECS, Fall 2006. Organized a week of informational and social orientation activities for new graduate students in the department.
• Graduate Resident Tutor, MIT Fall 2006 – Spring 2007. Served as a mentor as a graduate resident in the undergraduate dormitories; organized educational and social events.
• Hall Chair, MIT Spring 2004 – Fall 2005. Contributed to various aspects of hall government; including treasury management, social events, and room assignments.
• Officer, Club Sports Council, MIT 2002-2003. One of five students elected to represent and govern club sports at MIT; Athletics Gold Award for service (also MIT Taekwondo President Spring 2002 – Spring 2005).

• Postdoctoral:
  • Named one of IEEE Artificial Intelligence 10 to Watch (2013)
  • NSF CiTraCS Postdoctoral Fellowship recipient (2012)
  • Invited participant at the Rising Stars in EECS workshop, organized by MIT (2012).
• Graduate:
  • Hugh Hampton Young Fellowship recipient (2010-2011)
  • Honor Society Memberships: Phi Beta Kappa, Sigma Gamma Tau (aerospace honors society), Sigma Pi Sigma (physics honor society)
  • Marshall Scholar (2006)
  • Trinity Prince of Wales Research Student, alongside Trinity College External Research Studentship (2007)
  • NDSEG Fellowship recipient (2005)
  • NSF Graduate Fellowship recipient (2005)
• Undergraduate:
  • Honor Society Memberships: Phi Beta Kappa, Sigma Gamma Tau (aerospace honors society), Sigma Pi Sigma (physics honor society)
  • Awards: Goddard Research Award for best research project at the NASA Academy (2004), Manufacturing Award for undergraduate junior-senior design project (2005), Athletics Gold Award for Service for founding Club Sports Council (2005), Todd Anderson Teaching Award for excellence in teaching in the MIT Experimental Studies Group (2005).

• Invited Speaker, February 2014, Duke University.
• Invited Speaker, December 2013, NIPS Workshop on Causal Reasoning. Tutorial of POMDPs for Causal Reasoning.
• Panelist, October 2013, Health 2.0 Conference. Machine Learning for Medical Data Panel.
• Guest Lecturer, October 2013, Harvard University, CS281: Advanced Machine Learning (advanced graduate course). Prepared and presented a lecture on Monte Carlo techniques.
• Speaker, July 2013, BIGG Fellows Program at Harvard Medical School. Machine Learning for Discovering Phenotypes in Autism Spectrum Disorders.
• Speaker, May 2013, Northeastern University. Bayesian Nonparametric Methods for Timeseries Analysis.
• Speaker, March 2013. Vecna. Characterizing Temporal Patterns in Autism Spectrum Disorder from Electronic Health Records.
• Invited Speaker, September 2012. Institute for Computational and Experimental Research in Mathematics at Brown University. Bayesian nonparametric Approaches to Reinforcement Learning in Partially Observable Domains.
• Guest Lecturer, October 2011. Havard University. CS281: Advanced Machine Learning. Presented two lectures on inference in time series.
• Speaker, July 2011. Wellesley College, Summer Seminar Series. Towards Better AI: Using Bayesian Nonparametric Methods to Build More Flexible Agents.
• Guest Lecturer, Planning Under Uncertainty Course; Lincoln Labs June 2011. Bayesian Reinforcement Learning for Dialog Management.
• Speaker, April 2011. University of Toronto, Machine Learning Seminar. Bayesian Nonparametric Approaches to Reinforcement Learning in Partially Observable Domains.
• Speaker, March 2011. Rutgers University, Rutgers Laboratory for Real-Life Reinforcement Learning Group. Bayesian Nonparametric Approaches to Reinforcement Learning in Partially Observable Domains: The Nuts and Bolts.
• Speaker, November 2011. Tufts University, Computer Science Seminar Series. Bayesian Nonparametric Approaches to Reinforcement Learning in Partially Observable Domains.
• Speaker, November 2010. University of Massachusetts Amherst, Machine Learning Seminar Series. Bayesian Nonparametric Approaches to Reinforcement Learning in Partially Observable Domains.
• Guest Lecturer, 16.420 Planning Under Uncertainty; MIT Fall 2010; Presented two guest lectures, one on inference in time-series models and one on Bayesian approaches to learning time-series models for a graduate level course.
• Speaker, April 2010, Brown University, Computer Science Seminar Series. Efficient Inference for the Indian Buffet Process.

• Volunteer Analyst, Statistics without Borders. 2009—present. Projects: Re-analyzed data from a study on the effectiveness of maternal health education on social and health outcomes for CARE in Bangalore, India (Winter 2011). Analyzed influences on choices surrounding the consumption of animal products for the Farm Sanctuary (Fall 2013).
• Volunteer Analyst, Learning Unlimited, 2011-2012. Organized focus groups to determine what aspects of MIT's Educational Studies Program's events had the most lasting effects on students.
• Expert reviewer for a report on the Liberian Truth Commission (Bird, Annie. 'A Preliminary Assessment of the Impact of the Liberian Truth and Reconciliation Commission,' An independent evaluation undertaken as part of the Human Rights Data Analysis Group (HRDAG) at Benetech's grant from the United States Department of State Bureau for Democracy, Human Rights and Labor (DRL), January 2010).
• Statistical consultant for evaluating effectiveness of various diarrhea treatment programs in Africa (Millenium Villages, Winter 2010).

• Speaker, Maggie L. Walker Governor's School, Spring 2011. Invited talk for the Mu Alpha Theta Math Honors Society on Bayesian Nonparametric Methods for Reinforcement Learning; guest lecturer for the Linear Algebra and Math Modeling classes.
• Speaker, MIT Women's Initiative, MIT Winter 2011. Visited middle and high schools in Brockton and gave lectures encouraging girls to consider careers in engineering. Combined motivational speaking with technical hands-on activities.
• Speaker, Young Jain Convention 2010, 2012. Spoke to high-school and college students on incorporating Jain values into daily situations as well as core theological principles.
• Educational Studies Program, MIT Fall 2002 - Present. Served as Co-chair, Treasurer, Publicity Chair. Directed SAT prep and enrichment programs for over 1000 high school students each and managed $60K cashflows. As a teacher, have taught SAT prep; seven week enrichment courses on statistics, elections and game theory, and creative writing; and one-day classes on a broad variety of topics ranging from flow algorithms and stochastic processes to essay writing and philosophy.
• Intern, Science Museum of Virginia, Richmond VA, Summer 2003. Developed sound and magnet demonstrations to educate museum visitors.

• Addir Fellow, Fall 2009-Spring 2011. Participated in interfaith dialog discussions across campus.
• Coffeetalk organizer, Spring 2010-Spring 2011, MIT. Helped run a volunteer student group that organized weekly deep discussion with free tea and coffee.
• Cafe Project volunteer, Fall 2008-Spring 2009, University of Cambridge. Volunteered at a student-run cafe that provided an alcohol-free late-evening social option for the community.
• Odyssey of the Mind coordinator, Governor’s School, Richmond VA, 1998-2001. School organizer and Global Champions 2001. Odyssey of the Mind is a year-long competition combining engineering, arts, and awful puns.
• Math Contest in Modeling, COMAP, 2000 - 2002. Modeled safe aircraft separation, optimal hurricane evacuation routes, and airline overbooking. Published in UMAP (highest honor).
• Yearbook Editor, Governor's School, Richmond VA, 1999-2001. Directed a completely student-run staff, including teaching new members yearbook skills, managing deadlines, and working on the book itself (including cover art).

• Relevant Coursework: Inference and Information, Algorithms for Estimation and Inference, Complex Digital Systems, Randomized Algorithms, Advanced Algorithms, Machine Learning, Communication Systems, Signals and Controls, Autonomy and Decision Making, Machine Vision, Optical Astronomy Lab, Unified Engineering, Non-Equilibrium Thermodynamics, Space Systems Design Lab, Aerospace Projects Lab, Complex Variables, Special Relativity and Quantum Mechanics, Negotiation in the Public Sector
• Software/Programming: MatLab/Simulink, R, Python, LaTex; some experience with Scheme, Ada95, C++, Java, Verilog, Bluespec
• Technical Skills: Basic hand and machine tools, circuitry, and artistic media
• People Skills: Leadership and teamwork, organization and project management, teaching and mentoring, certification as a mediator, coursework in public sector negotiation.