Naoki Egami is Assistant Professor in the Department of Political Science at Columbia University. Egami specializes in political methodology and develops statistical methods for questions in political science and the social sciences. His research has focused on causal inference from experimental and observational data, spatial and network analysis, and the development of machine learning methods for the social sciences.
Egami won the 2019 Gosnell Prize for the best work in political methodology presented at any political science conference during the preceding year. In 2017, he also received the John T. Williams Dissertation Prize for the best dissertation proposal in political methodology. His work has appeared or is forthcoming in various academic journals, such as American Journal of Political Science, Political Analysis, Journal of the American Statistical Association, and Journal of the Royal Statistical Society (Series A).
He received a PhD from Princeton University (2020) and a BA from the University of Tokyo (2015). He was a pre-doctoral fellow at Harvard University from 2018 to 2020. He also studied at the University of Michigan, Ann Arbor, as a visiting student in 2013.