Eli Ben-Michael

Eli Ben-Michael is an Assistant Professor in the Department of Statistics & Data Science and the Heinz College of Information Systems and Public Policy at Carnegie Mellon University. He is also affiliated with the CMU-NIST AI Measurement Science & Engineering Cooperative Research Center (AIMSEC). Previously, he was a Post-Doctoral Fellow at Harvard University in the Institute for Quantitative Social Science and the Department of Statistics.

Ben-Michael's research focuses on developing statistical and computational methods to solve practical issues in public policy and social science research. His work brings together ideas from statistics, optimization, and machine learning to create methods for credible and robust causal inference and data-driven decision making. His research spans multiple domains including healthcare policy, criminal justice reform, reproductive health, and education.

His scholarly work shows a strong emphasis on causal inference methodology, with particular attention to synthetic control methods, balancing weights, policy learning, and sensitivity analysis. His recent publications demonstrate applications across diverse fields including healthcare, economics, social policy, and criminal justice.

Ben-Michael completed his PhD in Statistics from UC Berkeley and earned his undergraduate degree in Computer Science and Statistics from Columbia University. His technical expertise includes developing open-source software, with contributions to the R packages 'augsynth' and 'multical' for synthetic control methods and multilevel calibration.