Key goals of his research program are: 1) Developing novel deep learning-driven biomedical technologies for translational clinical research and real-world evidence generation. 2) Generative artificial intelligence (AI), machine learning, medical imaging, and neural network capabilities with statistical reasoning to create personalized digital medicines that improve health outcomes. 3) Empowering patients, physicians, researchers, and regulators to make informed healthcare decisions.
Recent work from his lab has been published in Cell Reports Methods, Nature Digital Medicine, Cell press, Journal of American Medical Association, leading machine learning conferences, and workshop proceedings of The National Academies of Science Engineering and Medicine. Pratik serves as an expert reviewer for national grant panels on emerging technologies, and on advisory committees for generative AI regulation with government agencies and nonprofit foundations. Pratik has BS, MS, and Ph.D. degrees in biological and data 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 research here.
Watch Pratik's TED talk on biomarker prediction from low-cost images using machine learning here.