معرفی
Evan T.R. Rosenman is an Assistant Professor of Statistics at Claremont McKenna College’s Mathematical Sciences Department. Previously, he was a Postdoctoral Fellow at Harvard’s Data Science Initiative, affiliated with the Department of Statistics and the Institute for Quantitative Social Sciences. He earned his Ph.D. in Statistics from Stanford University in 2020, advised by Art Owen and Mike Baiocchi. His research focuses on causal inference, particularly hybridizing observational and experimental data to estimate causal effects, with applications in political science, public health, and gender-based violence prevention.
His academic journey includes teaching roles as an instructor for STATS/CME 195 (R programming) at Stanford and as a teaching assistant for courses in statistical learning, linear models, and machine learning. He has contributed to open-source projects like the wru package for Bayesian racial category prediction using surnames and geolocation.
Rosenman’s work spans methodological advancements in combining datasets, robust experimental design, and addressing census data challenges. His publications address topics such as recalibrating predictive probabilities, race imputation via Bayesian methods, and mitigating bias in sensitive topic trials. Collaborations include studies on sexual assault prevention in Kenyan informal settlements and policy evaluations related to the U.S. Census’s differential privacy system.
Though no specific grants or awards are listed, his research demonstrates significant contributions to causal inference and applied statistics, with a focus on societal impact in health and policy domains. His work often bridges theoretical statistics and real-world applications, emphasizing interdisciplinary relevance.
