Pratik Shah

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Pratik Shah is a Principal Investigator and Principal Research Scientist at the Massachusetts Institute of Technology. His research creates novel intersections between engineering, medical imaging, machine learning, and medicine to improve health and diagnose and cure diseases.

Key goals are: 1) Novel medical technologies for translational clinical and biomedical research and real world impact; 2) Augmenting artificial intelligence (AI), machine learning (ML), medical imaging and neural network capabilities for personalized digital medicines and improving health outcomes; and 3) Empowering patients, physicians, researchers, and regulators for making informed healthcare decisions. Pratik’s graduate and postdoctoral research have contributed to the discovery of a vaccine component to prevent pneumococcal (Streptococcus pneumoniae) diseases; the identification of new pathways, technologies, and metabolites as antimicrobials to target gastrointestinal infections; and a non-profit organization to deploy a low-cost water quality test for the developing world. Past acknowledgments include the American Society for Microbiology’s Raymond W. Sarber National Award, a Harvard Medical School and Massachusetts General Hospitals ECOR Fund for Medical Discovery postdoctoral fellowship, coverage by leading national and international news media outlets. Pratik has been an invited discussion leader at Gordon Research Seminars; a speaker at American Association for the Advancement of Sciences, Cold Spring Harbor Laboratories, Gordon Research Conferences, The National Academies of Sciences, Engineering and Medicine, TED and IEEE bioengineering conferences; and a peer reviewer for leading scientific publications and funding agencies. Pratik has BS, MS, and Ph.D. degrees in biological sciences and completed fellowship training at Massachusetts General Hospital, the Broad Institute of MIT and Harvard, and Harvard Medical School.

Read more about Pratik's ongoing research at MIT here.

Watch Pratik's TED talk on biomarker prediction from low-cost images using machine learning here.