Janie Coulombe from McGill University is the recipient of the Pierre Robillard Award of the Statistical Society of Canada. This prize recognizes the best PhD thesis in probability or statistics defended at a Canadian university in a given year. The criteria used in selecting the winner of the Pierre Robillard Award include the originality of ideas and techniques, the possible applications and their treatment, and the potential impact of the work. The award is named in memory of Professor Pierre Robillard, an outstanding dynamic young statistician at the Université de Montréal, whose untimely death in 1975 cut short what promised to be a highly distinguished career.

Janie’s thesis, entitled “Causal Inference on the Marginal Effect of an Exposure: Addressing Biases due to Covariate-Driven Monitoring Times and Confounders”, was written under the co-supervision of Professors Erica Moodie and Robert Platt.

Janie Coulombe is currently a postdoctoral researcher at McGill University, working in collaboration with Dr. Erica E. M. Moodie and Dr. Susan M. Shortreed on causal inference and missing data imputation. Prior to that, she earned a bachelor’s in mathematics and a master’s in statistics from the Université de Montréal. After obtaining her master’s degree, Janie worked for two years as an analyst at the Lady Davis Institute of the Jewish General Hospital in Montréal. There, she learned to work with complex, large datasets not meant for research purposes and discovered a passion for biostatistics and causal inference. She then went on to pursue doctoral studies at McGill University, under the supervision of Dr. Erica Moodie and Dr. Robert Platt, and earned in 2021 a PhD in biostatistics from the Department of Epidemiology, Biostatistics and Occupational Health. Her doctoral work focused on causal inference with imperfect longitudinal data. It proposed new estimators for the average treatment effect in settings where the observation times of an outcome of interest are covariate-dependent. It also assessed a few different extensions that can account for other complex data scenarios.

The citation for the award reads:

"To Janie Coulombe, for the thesis entitled 'Causal Inference on the Marginal Effect of an Exposure: Addressing Biases due to Covariate-Driven Monitoring Times and Confounders', written under the co-supervision of Professors Erica Moodie and Robert Platt."

Paul Y. Peng was principally responsible for this information.