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Rahul Ladhania is an Assistant Professor of Health Informatics at the University of Michigan School of Public Health (effective August 2020). His research is in the area of causal inference and machine learning in health policy. A large part of his work focuses on learning optimal treatment rules and estimating heterogeneous effects of policy, digital and/or behavioral interventions on patient/user behavior and health outcomes in complex empirical settings using statistical machine learning methods.

Rahul completed his PhD in Public Policy at Carnegie Mellon University, where his primary advisor was Amelia Haviland.  Prior to joining Michigan, he was a post-doctoral researcher with The Behavior Change For Good Initiative (BCFG) at The Wharton School of the University of Pennsylvania. Currently affiliated as a visiting scholar with BCFG, Rahul co-leads the machine learning team with Lyle Ungar, Katherine Milkman, Sendhil Mullainathan, and Jann Spiess. Rahul is also an affiliate faculty with the Center for Health Incentives and Behavioral Economics (CHIBE) at the University of Pennsylvania.