About James Diao

James Diao grew up amid Chinese restaurants, street signs, and supermarkets in the largest Chinatown of Houston, Texas. He was first raised by his grandparents, who delighted in teaching him parodies of famous poems to recite. Later, when his grandparents returned to Jiangxian, James continued to spend the summers with them and his extended family. In the United States, James’s family later moved to Fort Bend, Texas, among the most diverse counties in the country, where he met classmates, teachers, and pastors with very different life experiences from his own. 

Inspired by his experiences in the Texas Medical Center and his parents’ love of programming, James soon became interested in the intersection of health and technology. These interests drove James throughout his work at Apple, where he led projects to validate wearable health features in diverse populations; at PathAI, where he built deep learning models to predict molecular features from cancer histology slides; at the University of Cambridge, where he studied science policy as a Churchill Scholar; and at Harvard, where he researched the impacts of clinical guidelines on marginalized groups. James’s lead author research in NEJM and JAMA systematically compared race-based and race-free equations for kidney function and lung function. His other works on machine learning and precision medicine have appeared in Cell, Cell Systems, Human Molecular Genetics, and Nature Communications.

James is currently a resident physician in internal medicine at Brigham and Women's Hospital and Berkowitz postdoctoral fellow in the Harvard Medical School Department of Biomedical Informatics. He is a proud alumnus of the Harvard-MIT Program in Health Sciences and Technology, where he was the 22nd person in the history of Harvard Medical School to graduate with highest honors (summa cum laude). Following his medical and scientific training, James hopes to give voice to patient perspectives in the development and evaluation of healthcare technology.


  • BS in Statistics and Data Science; Molecular Biophysics and Biochemistry, Yale University
  • MPhil in Public Policy, University of Cambridge
  • MD in Medicine, Harvard University

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