Summary
Hamsa Bastani is an Associate Professor with tenure at The Wharton School who develops novel machine learning methods for data-driven decision-making, with applications spanning healthcare operations, revenue management, and social good. He specializes in transfer learning for settings with limited data—enabling predictive analytics for small cohorts, dynamic pricing across related products, and faster clinical trials via surrogate outcomes. His work bridges rigorous academic research and real-world impact through consulting engagements with organizations like Meta and MACRO-EYES, and a postdoctoral fellowship at IBM. Trained in physics and electrical engineering (PhD Stanford; MA and AB summa cum laude from Harvard), he combines theoretical depth with practical algorithm design. He is also engaged in algorithmic accountability and using big data to detect and mitigate social and environmental harm, bringing an uncommon focus on ethical deployment alongside technical innovation.
8 years of coding experience
5 years of employment as a software developer
Master of Arts (M.A.), Physics, Master of Arts (M.A.), Physics at Harvard University
Bachelor of Arts (B.A.), Physics and Mathematics, Summa Cum Laude, Bachelor of Arts (B.A.), Physics and Mathematics, Summa Cum Laude at Harvard College
Doctor of Philosophy (PhD), Electrical Engineering, Doctor of Philosophy (PhD), Electrical Engineering at Stanford University