Bio

Avi Feller is an associate professor in the Goldman School of Public Policy and the Department of Statistics at UC Berkeley. He develops statistical methods for causal inference, with an emphasis on weighting, synthetic controls, and the design and analysis of experiments. He works with collaborators to apply these methods to policy evaluation in education and health, and to the evaluation of AI systems. His research has appeared in methodological journals (such as Journal of the American Statistical Association, Journal of the Royal Statistical Society, and Econometrica), in machine learning conferences (such as NeurIPS and ICML), and in interdisciplinary journals like the Proceedings of the National Academy of Sciences.

Outside of academia, Feller is a research consultant at Adobe and was previously a visiting researcher at Google. He also co-founded EveryDay Labs, an edtech company focused on reducing student absenteeism (acquired by Newsela in 2026).

Feller has received multiple awards for his work, including the COPSS Emerging Leader Award, the SREE Early Career Award, the American Statistical Association’s Outstanding Statistical Application Award, and the Mid-Career Award from the ASA Social Statistics Section. He received a PhD in statistics from Harvard University, an MSc in Applied Statistics from Oxford University as a Rhodes Scholar, and a BA from Yale University. Prior to his doctoral studies, he worked as a policy official in the White House Office of Management and Budget.