معرفی
Eli Ben-Michael is an Assistant Professor jointly appointed in the Department of Statistics & Data Science and the Heinz College of Information Systems and Public Policy at Carnegie Mellon University. He is affiliated with the CMU-NIST AI Measurement Science & Engineering Cooperative Research Center (AIMSEC). Previously, he was a postdoctoral fellow at Harvard University and earned his PhD in Statistics from UC Berkeley.
Education:
- PhD in Statistics, UC Berkeley (2016–2020)
- Bachelor’s in Computer Science & Statistics, Columbia University
Research Interests: Dr. Ben-Michael focuses on developing statistical and computational methods for causal inference and data-driven policy evaluation. His work bridges statistics, machine learning, and optimization to address challenges in public policy, healthcare equity, and social science. Key areas include synthetic control methods, balancing weights, safe policy learning, and causal effects in natural language processing. His research has been applied to topics such as gun control policies, healthcare disparities, and pre-trial risk assessment.
Key Contributions: His methodological innovations include the Augmented Synthetic Control method and tools for policy learning under uncertainty. He has developed open-source R packages like augsynth and balancer to implement his methods.
Labs/Teams: He is part of the AIMSEC collaboration, advancing AI measurement science, and contributes to interdisciplinary teams studying policy impacts in healthcare, education, and criminal justice.
