-Faculty Member and Professor, Pathology, Director Computational Medicine Research Program, School of Medicine
-Faculty Member and Professor, Biomedical Engineering, The Henry Samueli School of Engineering
-Faculty Member and Professor, Electrical Engineering and Computer Science, The Henry Samueli School of Engineering
Research Overview: Dr. Pratik Shah is the Principal Investigator and director of a computational medicine research program. The lab focuses on hypothesis-driven deep learning, generative AI, biomedical engineering, and clinical research to develop medical technologies for diagnosing and treating cancer and infectious diseases. This research invents novel deep learning, biological, and statistical methods to tackle challenges in personalized medicine. Dr. Shah's work includes advancements in generating medical images for unbiased, patient-centered care, and evaluating the impact of clinical decision-making on infectious diseases and antimicrobial therapy, within a unified theoretical and methodological framework. Recent work from the lab has been published in Cell Press journals including Cell Reports Methods and Trends in Pharmacological Sciences; Nature Digital Medicine; the Journal of the American Medical Association Network; leading machine learning conferences, and workshop proceedings of The National Academies of Sciences, Engineering, and Medicine. Dr. Shah and his research group are developing a dynamic, living-systems framework for computational medicine, transitioning from static models to real-time, systems-wide perspectives on molecular and clinical processes. Their goal is to invent, clinically validate, and deploy trustworthy generative AI medical technologies that improve patient outcomes and public health.
Short Bio: Dr. Pratik Shah is a professor at the University of California and the principal investigator and director of a computational medicine research program. Dr. Shah holds academic appointments in Pathology & Laboratory Medicine and joint appointments in Electrical Engineering & Computer Science and Biomedical Engineering. He serves as a Special Government Employee for the U.S. Food and Drug Administration and was an invited expert panelist at the inaugural FDA Digital Health Advisory Committee meeting on generative AI-enabled devices. In 2026, he delivered the plenary keynote at SCOPE X, a national conference on data strategies and AI innovation in clinical research. Recent work from his lab has been published in Cell Press journals including Cell Reports Methods and Trends in Pharmacological Sciences; Nature Digital Medicine; the Journal of the American Medical Association Network; leading machine learning conferences, and workshop proceedings of The National Academies of Sciences, Engineering, and Medicine. Previously, Dr. Shah was a Principal Investigator at the Massachusetts Institute of Technology (MIT), where he led a computational medicine research program. He also served as principal investigator for a memorandum of understanding with the U.S. FDA and MIT, aimed at establishing AI and machine learning research ecosystems for clinical development. Dr. Shah holds a BS, MS, and PhD in biological and data sciences and completed postdoctoral fellowship training at the Broad Institute of MIT and Harvard, Massachusetts General Hospital, and Harvard Medical School.