Professor Collin M. Stultz Professor Collin M. Stultz | RLE Bio | RLE Video

Dr. Collin M. Stultz is a Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), a faculty member in the Harvard-MIT Division of Health Sciences and Technology, a Professor in the Institute of Medical Engineering and Sciences at MIT, a member of the Research Laboratory of Electronics (RLE), and an associate member of the Computer Science and Artificial Intelligence Laboratory (CSAIL). He is also a practicing cardiologist at the Massachusetts General Hospital (MGH). Dr. Stultz received his undergraduate degree in Mathematics and Philosophy from Harvard University; a PhD in Biophysics from Harvard University; and a MD from Harvard Medical School. He did his internship, residency, and fellowship at the Brigham and Women’s Hospital in Boston. His scientific contributions have spanned multiple fields including computational chemistry, biophysics, and machine learning for cardiovascular risk stratification. He is a member of the American Society for Biochemistry and Molecular Biology and the Federation of American Societies for Experimental Biology and he is a past recipient of a National Science Foundation CAREER Award and a Burroughs Wellcome Fund Career Award in the Biomedical Sciences. Currently research in his group is focused on the development of machine learning tools that can guide clinical decision making.


Ridwan Alam, PhD

Ridwan Alam is a Visiting Scientist at the Research laboratory of Electronics (RLE) in the Massachusetts Institute of Technology (MIT), and a Research Fellow at the Cardiovascular Research Center (CVRC) in the Massachusetts General Hospital (MGH). He received his PhD in Electrical Engineering from the University of Virginia, after acquiring his MS in ECE from the University of Oklahoma and his BS in EEE from Bangladesh University of Engineering and Technology. Ridwan’s research contributions and interest span the broad area of signal processing and machine learning for health applications; including areas such as HealthAI, Smart and Connected Health, Biomedical Health Informatics, and Digital Health. He is a member of the Institute of Electrical and Electronics Engineers (IEEE), IEEE Engineering in Medicine and Biology Society (EMBS), and Association for Computing Machinery (ACM). His current research is focused on inferring physiological and behavioral health parameters from non-invasive sensing modalities toward designing systems for clinical decision making.


Wangzhi Dai

Wangzhi Dai is a graduate student in the Department of Electrical Engineering and Computer Science. He is primarily interested in developing computational tools to help clinical decision making. Currently he is working on risk stratification of patients with acute coronary syndrome using a machine learning approach. Before coming to MIT, He earned his Bachelor’s at Peking University in 2017.




Daphne Esther Schlesinger

Daphne is working towards her PhD in the Medical Engineering and Medical Physics program at HST, with a focus in Computer Science. She is interested in developing interpretable clinical decision support models for applications in cardiovascular disease. Before starting at MIT, she received a BS in Biomedical Engineering and in Physics from Johns Hopkins University.



Aniruddh Raghu

Aniruddh is a PhD student in the Department of Electrical Engineering and Computer Science, co-advised by Prof. Collin Stultz and Prof. John Guttag. He is interested in applications of machine learning to healthcare problems, including causal inference in medicine and developing tools for clinical risk stratification. Before coming to MIT, Aniruddh completed his Bachelor’s and Masters degrees at the University of Cambridge in 2018.




Angela C Zhang

Angela Zhang is an undergraduate majoring in Computer Science and Mathematics.

Clinical Coordinator at MGH

Cara Berg

Cara Berg is an aspiring medical student working as a Clinical Research Coordinator in her gap years. She is currently coordinating multiple trials investigating Hypertrophic Cardiomyopathy. These trials are principally investigated by Dr. Stultz of MIT, Dr. Fifer of MGH, and Dr. Tower-Rader of MGH.

Administrative Assistant

Megumi Masuda-Loos

Megumi is the administrative assistant for Prof. Collin Stultz. She provides administrative support to Prof. Collin Stultz and his students.



Alicia Rodriguez

Alicia is a graduate student towards a Master of Science in Engineering and Management at the Integrated Design Management program at the Massachusetts Institute of Technology (MIT). She worked for 6 years in the semiconductor industry at Hewlett Packard Networking and Teradyne Inc. Currently, her work is gender-focused, oriented towards uncovering gaps with data to identify and improved care of cardiovascular diseases patients at high risk.



Katherine W Young

Katherine Young is a graduate student in the Department of Electrical Engineering and Computer Science at MIT. Currently she is working with physician-scientists to develop optimal treatment regimens for patients with congestive heart failure using reinforcement learning. She received her B.S. in Computer Science and Music from MIT in 2018, and in her free time enjoys playing the violin and running long distances.



Kristy A Carpenter

Kristy Carpenter is an undergraduate majoring in Computer Science and Molecular Biology. She is developing machine learning methods to identify non-hemolytic peptides that have antimicrobial properties.  Her research interests include machine learning, molecular dynamics simulations, and drug discovery.



Paul Myers

Paul Myers is a graduate student in the Department of Electrical Engineering and Computer Science. He is currently developing new computational biomarkers for use in statistical models to identify patients at a high risk of cardiovascular death.



Erik Reinertsen

Erik is a postdoctoral research fellow at MIT and the Massachusetts General Hospital. He builds machine learning algorithms to read ECGs, predict cardiovascular emergencies from physiological time series data, and phenotype shock. Previously Erik interned on the investment team at at Takeda Ventures and co-founded a non-profit to help startups launch pilots at academic medical centers. He holds an MD from Emory University, a PhD in biomedical engineering from Georgia Tech, and a BS in bioengineering from UCLA.

Harlin Lee    
Molly Schmidt    
Shuo Gu    
Virginia Burger    
Yun Liu   Deep Learning Resident at Google (Brain Team)
Sarah J. Bowman   Post-doctoral fellow at Los Alamos
Linder Candida DaSilva   Professor, Portal da Universidade Federal de Mato Grosso
Thomas Gurry   Post-doctoral fellow, Eric Alm group
Orly Ullman    
Munishika Kalia    
Mathura Sridharan   Consultant
Gordon Lu   Medical Student
Elaine Gee   Post-doctoral fellow at Wyss Institute, Harvard University
Charles Fisher   Post-doctoral fellow at BU
Sophie Walker    
Priya Parayanthal   Business Analyst at McKinsey & Company
Joyatee Sarker   MDPhD student at Indianapolis
Ramon Salsas-Escat   Industry
Christine Phillips-Piro   Post-doctoral fellow, Berkeley / Faculty in Chemistry at Franklin & Marshall College
Paul Nerenberg Post-doctoral fellow, Berkeley / Visiting Assistant Professor of Physics, Clairmont McKenna College
Austin Huang   Post-doctoral fellow, Brown Univ. / Assistant Professor of Resarch at Brown
Christian Schubert   Post-doctoral Fellow, Harvard Medical School
Amelia Thomas   Graduate student, Tufts Univ.
Jennifer Lin   Working at Google
Jane Lu   Working at Google
Veena Venkatachalam   MD/PhD Student at Harvard Medical School
William Wyatt   MIT Undergraduate
Anjali Muralidhar   MIT Undergraduate
Steven Pennybaker   MIT Undergraduate
Nebiyat Tsegaye   MIT Undergraduate
Joy Okpala   MIT Undergraduate
Frank Yang