Prasad Patil

Prasad Patil is an Assistant Professor of Biostatistics at the School of Public Health and a Junior Faculty Fellow of the Hariri Institute at Boston University. Patil received his PhD in Biostatistics from Johns Hopkins University. He conducted his postdoctoral research at the Dana-Farber Cancer Institute and Harvard School of Public Health where he developed and evaluated ensemble methods for replicable risk prediction in ovarian cancer genomic data.

His research focuses are multi-study prediction and causal inference in genomics and air pollution, machine learning applications in opioid surveillance and kidney disease categorization, and questions surrounding reproducibility and replicability in the conduct of scientific research.

Research Interests: machine learning, multi-study, generalizability, reproducibility, replicability

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