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Michael Wallace is an Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. He received his PhD from the London School of Hygiene and Tropical Medicine in 2012, where his thesis focused on classical covariate measurement error. He has also earned an MSc in Statistics from University College London and an MA in Mathematics from Trinity College, Cambridge. From 2013 to 2016, he was a postdoctoral fellow at McGill University, collaborating with Erica Moodie and David Stephens. His earlier experience includes working as a statistician in a multi-disciplinary team at City University, London, where he studied treatment for childhood eye diseases. His primary research interest lies in causal inference, with a particular focus on dynamic treatment regimes and personalized medicine. Specifically, he works with longitudinal datasets to derive methodologies that help identify sequences of treatment decisions that yield expected outcomes. He is generally interested in finding new ways to apply methods from statistics to address novel problems in real-world data analysis.
McGill University • Montreal, Canada
Conducted research in collaboration with Erica Moodie and David Stephens.
City University, London • London, UK
Worked as part of a multi-disciplinary team studying treatment for childhood eye diseases.
Includes fields like Clinical, Cognitive, Developmental, and Industrial/Organizational Psychology.