Vasilis Syrgkanis

Vasilis Syrgkanis is an assistant professor in Management Science and Engineering and (by courtesy) in Computer Science and Electrical Engineering at Stanford University. He leads the Stanford Causal AI Lab and is an Associate Director of the Stanford Causal Science Center. His research interests lie in the areas of machine learning, causal inference, econometrics, online and reinforcement learning, game theory/mechanism design and algorithm design.

Until August 2022, he was a Principal Researcher at Microsoft Research, where he led the development of the EconML library, a widely used open-source library for causal machine learning. His research has received best paper awards at the ACM Conference on Economics and Computation (ACM EC), the Conference on Neural Information Processing Systems (NeurIPS) and the Conference on Learning Theory (COLT). He is the recipient of a 2022 Amazon Research Award, a 2023 Google Research Scholar award, the 2023 Bodossaki Distinguished Young Scientist award and a 2024 NSF CAREER award. He is the author of more than 80 research publications and of the book Applied Causal Inference Powered by ML and AI.