Rahul Ladhania

Rahul Ladhania is an Assistant Professor with joint appointments in Health Informatics, Health Management and Policy, and Biostatistics at the University of Michigan School of Public Health.

His educational background includes:

• PhD in Public Policy and Management from Carnegie Mellon University
• MPhil in Public Policy and Management from Carnegie Mellon University
• B.Tech in Metallurgical and Materials Engineering from Indian Institute of Technology Madras

Dr. Ladhania's research focuses on causal inference and machine learning applications in public and behavioral health. He specializes in adapting machine learning methods for learning optimal treatment rules and estimating heterogeneous treatment effects in complex policy and behavioral health settings. His work bridges advanced statistical methods with practical health policy applications, with emphasis on personalized interventions and policy evaluation. He has particular expertise in analyzing the effects of healthcare policy changes, such as Medicaid expansion, on population health outcomes.

His publications demonstrate expertise in applying machine learning to health behavior and policy evaluation, spanning both methodological development in causal inference and practical applications to pressing public health issues including Medicaid policy effects on emergency department utilization and methods for personalizing behavioral interventions.

Dr. Ladhania teaches courses on artificial intelligence in healthcare policy and data management and visualization, helping students develop practical skills in applying data science methods to health policy challenges.