Bio

Mohsen Bayati is the Carl and Marilynn Thoma Professor of Operations, Information and Technology at the Stanford Graduate School of Business, and the Business School Trust Faculty Fellow for 2026-27. He holds courtesy appointments in Electrical Engineering and Radiation Oncology, and is a faculty affiliate of Stanford HAI and a member of Bio-X. He is currently a visiting faculty researcher at Google. Earlier he worked with Amazon on pharmacy safety, language models and experimentation, and with Turing on the evaluation of AI and agentic systems.

His research asks what has to be true before an AI system can be trusted with a consequential decision. He works on alignment and oversight methods that give a deployed model the properties its users actually need, on causal inference and experiment design for settings where units interfere with each other, and on the theory of sequential decision-making under uncertainty. Much of the applied work is done with clinicians, and several of the resulting models have been deployed in hospitals and pharmacies.

He received a BS in mathematics from Sharif University of Technology and a PhD in electrical engineering from Stanford University, then was a postdoctoral researcher at Microsoft Research and at Stanford. His work has received the INFORMS Health Applications Society Pierskalla best paper award in 2014 and 2016, the INFORMS Applied Probability Society best paper award in 2015, an NSF CAREER award, and the 2024 PhD Faculty Distinguished Service Award at Stanford GSB. He delivered the INFORMS Applied Probability Society Distinguished Lecture in 2025, and is an associate editor at Management Science and Stochastic Systems.

Mohsen Bayati is the Carl and Marilynn Thoma Professor of Operations, Information and Technology at the Stanford Graduate School of Business. He works on the mathematics of deploying AI in high-stakes settings: alignment and human oversight, experiment design under interference, and sequential decision-making. His research has appeared in Nature Medicine, PNAS, Management Science, Operations Research and NeurIPS, and has been recognized with the INFORMS Pierskalla and Applied Probability Society best paper awards and an NSF CAREER award.