The Institute of Quantitative Social Sciences
From an early age, Evan Rosenman has been interested in problems at the interface of the mathematical sciences and public policy. Evan earned his undergraduate degree at Harvard, where he majored in Applied Mathematics. Evan subsequently did a stint as a software Product Manager in Washington, D.C. Finding himself drawn to the academic study of data science, he earned a part-time Master's Degree in Statistics and Mathematics from Georgetown. In 2015, Evan moved to California to begin a doctorate in Statistics at Stanford, which he completed in 2020. Evan's research interests have been motivated by the real-world challenges faced by statistical practitioners, and center on questions of causal inference. Throughout graduate school, he has also pursued data analytics opportunities with various progressive political organizations, including the Black Voters Matter Fund and the Morris County, NJ Democratic Committee. Outside of research, Evan enjoys stand-up comedy, cooking, and seeing movies.
Evan's methodological research focuses on causal inference, the use of statistics to estimate causal effects. He is interested in questions of “data fusion,” in which heterogeneous data sources are combined. In particular, he seeks to use observational data to design better experiments, and use observational and experimental data together to estimate the impact of a treatment of interest. Evan also has substantive application interests in the areas of health policy and political science. He is interested in large-scale experiments for health interventions, and the associated questions of program evaluation. Evan is also interested in the analysis of political elections and the efficacy of voter mobilization efforts. He seeks to develop causal inference methodologies that can be utilized by practitioners in these domains.