Rahul Ladhania is an Assistant Professor of Health Informatics at the University of Michigan School of Public Health. His research is in the area of causal inference and machine learning in public and behavioral health. A large part of his work focuses on learning optimal treatment rules and estimating heterogeneous effects of policy, digital and behavioral interventions on patient/user behavior and health outcomes in real-world settings using statistical machine learning methods.
Rahul completed his PhD in Public Policy at Carnegie Mellon University, where his primary advisor was Amelia Haviland. He received his B.Tech from the Indian Instite of Technology Madras. Before 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 BCFG machine learning team. He is also an affiliate faculty with the Center for Health Incentives and Behavioral Economics (CHIBE) at the University of Pennsylvania.