Rushabh H. Doshi

Rushabh Hemang Doshi, MPH, MSc, is a medical student at the Yale School of Medicine whose work focuses on integrating large-scale epidemiology with multi-omic and translational research in metabolic disease. He uses statistical modeling and machine-learning approaches developed from national survey and registry data to build integrated models that combine clinical, imaging, and multi-omic features from the duodenum and liver. His long-term goal is to sub-phenotype diabetes and obesity, in the hopes of distinguishing patients whose disease is driven by duodenal signaling, hepatic lipid handling, or other pathways, and match them to targeted upstream interventions such as duodenal endoscopic procedures, GLP-1s, or combination strategies. His broader interests include artificial intelligence and medical device innovation, with an emphasis on patient-centered outcomes. He has been supported by a one-year research fellowship from the National Heart, Lung, and Blood Institute of the National Institutes of Health, the Richard K. Gershon Endowed Medical Student Research Fellowship, and an NIH Medical Student Research Training Fellowship, and has led multiple epidemiologic and methods-focused studies.

Rushabh received his BA from Johns Hopkins University and has been recognized by both the Baltimore and Los Angeles City Councils for community health initiatives. Before Yale, he completed an MSc in Medical Anthropology at the University of Oxford and an MPH at the Harvard T.H. Chan School of Public Health, working at Sabeti Labs at the Broad Institute on digital tools to connect vulnerable populations to resources during the COVID-19 pandemic. He hopes to become a physician-investigator leading large-scale clinical and community trials in gastroenterology, integrating AI, innovation, and health data to advance precision care in metabolic disease.