Lester Mackey is a Principal Researcher at Microsoft Research, where he develops machine learning methods, models, and theory for large-scale learning tasks driven by applications from climate forecasting, healthcare, and the social good. Lester moved to Microsoft from Stanford University, where he was an assistant professor of Statistics and, by courtesy, of Computer Science. He earned his PhD in Computer Science and MA in Statistics from UC Berkeley and his BSE in Computer Science from Princeton University. He co-organized the second place team in the Netflix Prize competition for collaborative filtering; won the Prize4Life ALS disease progression prediction challenge; won prizes for temperature and precipitation forecasting in the yearlong real-time Subseasonal Climate Forecast Rodeo; and received best paper, outstanding paper, and best student paper awards from the ACM Conference on Programming Language Design and Implementation, the Conference on Neural Information Processing Systems, and the International Conference on Machine Learning. He is a 2023 MacArthur Fellow, a Fellow of the Institute of Mathematical Statistics, a Fellow of the American Statistical Association, an elected member of the COPSS Leadership Academy, and the recipient of the 2023 Ethel Newbold Prize.

Lester serves as a General Chair for the 2024 Conference on Neural Information Processing Systems, as a Senior Meta-Reviewer for the International Conference on Machine Learning, as a Statistical Editor for the Proceedings of the National Academy of Sciences, and as an Associate Editor of the SIAM Journal on Mathematics of Data Science. He formerly served as an Associate Editor of the Annals of Statistics and as an Editor of Environmental Data Science and is currently a member of the American Statistical Association (ASA), the Association for the Advancement of Artificial Intelligence (AAAI), the Association of Computing Machinery (ACM), the Bernoulli Society, the Institute of Electrical and Electronics Engineers (IEEE), the Institute of Mathematical Statistics (IMS), the International Society for Bayesian Analysis (ISBA), and the Society for Industrial and Applied Mathematics (SIAM).