I’m an Assistant Professor of Biostatistics at McGill University with a joint appointment in the Department of Epidemiology, Biostatistics, and Occupational Health and the Department of Medicine. I’m also a Junior Scientist at the Research Institute of the McGill University Health Centre.
I’m broadly interested in the development of assumption-lean statistical methods and their application to quantitative problems in the health and life sciences. Assumption-lean procedures combine causal inference, machine learning, and semiparametric techniques to provide dependable statistical inference without relying on convenience assumptions. I’m also committed to the development of open-source statistical software and, more broadly, to the adoption of reproducible research practices. My most recent work has focused on developing causal machine learning methods for heterogeneous treatment effect discovery in clinical trial data.