Naoki Egami

Naoki Egami is an Associate Professor (with tenure) of Political Science at the Massachusetts Institute of Technology. He is also a faculty affiliate of the Statistics and Data Science Center in the Institute for Data, Systems, and Society (IDSS) at MIT and the Institute for Quantitative Social Science (IQSS) at Harvard. Egami specializes in political methodology and develops statistical methods for questions in political science and the social sciences. Specifically, he works on causal inference and machine learning methods. His current research programs focus on three areas: (1) External Validity, (2) Machine Learning and AI for the Social Sciences, and (3) Causal Inference with Network and Spatial Data.

His work has appeared or is forthcoming in various academic journals in political science, statistics, and computer science, such as American Political Science Review, American Journal of Political Science, Journal of the American Statistical Association, Journal of the Royal Statistical Society (Series B), Neurips, and Proceedings of the National Academy of Sciences (PNAS). His contributions have been recognized with various awards. In 2025, Egami received the Emerging Scholar Award from the Society for Political Methodology, which ``honors a young researcher, within ten years of their degree, who is making notable contributions to the field of political methodology.'' 

Before joining MIT, Egami was an Assistant Professor at Columbia University from 2020 to 2025. He received a Ph.D. from Princeton University (2020) and a B.A. from the University of Tokyo (2015).