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.
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Collin Stultz
Collin M. Stultz
Professor of Electrical Engineering and Computer Science, Electrical Engineering and Computer Science (EECS)
MIT's Collin Stultz: Professor of Electrical Engineering and Computer Science, Electrical Engineering and Computer Science (EECS).
77 Massachusetts Avenue
Room 36-796
Cambridge, MA 02139
Room 36-796
Cambridge, MA 02139
Keywords
molecular simulations, protein structure and dynamics, biophysics, disease models, atherosclerosis, Alzheimer's disease, rheumatoid arthritis, stochastic models, function optimization
molecular simulations, protein structure and dynamics, biophysics, disease models, atherosclerosis, Alzheimer's disease, rheumatoid arthritis, stochastic models, function optimization
Related News Links
01.27.2020
Technique reveals whether models of patient risk are accurate
10.15.2014
Stultz and Voldman are selected for Faculty Research Innovation Fellowships (FRIFs)