Stephen Bates

Assistant Professor

Stephen Bates is an Assistant Professor of AI and Decision-making in the MIT EECS department, working to understand uncertainty and reliable decision-making with data. In particular, he develops tools for statistical inference with AI models, data impacted by strategic behavior, and settings with distribution shift. In addition, he works on applications in the life sciences and sustainability.

Previously, he was a postdoctoral researcher with Michael I. Jordan in the UC Berkeley Statistics and EECS departments. He completed my Ph.D. in the Stanford Department of Statistics advised by Emmanuel Candès, where he was awarded the Theodore W. Anderson Theory of Statistics Dissertation Award. Before his Ph.D., he studied statistics and mathematics at Harvard University, and spent a year teaching mathematics at NYU Shanghai. Outside research, he enjoys triathlons, sailing, hiking, and reading speculative fiction novels.