We are pleased to announce that, effective March 1, 2025, Dr. Philippe Boileau has been jointly appointed to the Department of Epidemiology, Biostatistics and Occupational Health, as well as the Division of Clinical Epidemiology in the Department of Medicine. He is also a Junior Scientist at the Research Institute of the 黑料社 Health Centre, where he is a member of the Accelerating Clinical Trials 鈥� Clinical Trials Unit and the Centre for Outcomes Research and Evaluation. Prior to joining 黑料社, Dr. Boileau completed a PhD in Biostatistics at the University of California, Berkeley.
Dr. Boileau is 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 and machine learning techniques to avoid unjustified assumptions about data-generating processes, encouraging dependable statistical inference. He is also committed to the development of open-source statistical software and, more broadly, to the adoption of reproducible research practices. His recent work has focused on (1) developing of causal machine learning methods for treatment effect modifier discovery in clinical trial data and (2) using real-world evidence to inform clinical trial planning and conduct.