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Mehdi Dagdoug is an Assistant Professor in the Department of Mathematics and Statistics at McGill University in Montréal, Canada. He completed his Ph.D. in Mathematics at the University of Bourgogne Franche-Comté, focusing on statistical learning and high-dimensional sampling. His doctoral thesis work, conducted under the supervision of Camelia Goga and David Haziza, addressed the complexities in statistical inference methods for survey sampling and treatment of missing data. Specifically, Dagdoug's research interests lie at the intersection of survey sampling theory and statistical learning, developing rigorous inference methods in high-dimensional settings. He has been involved in tackling complex estimation problems while utilizing statistical learning tools to study the theoretical properties of resulting procedures. Dagdoug is also committed to teaching, currently delivering courses on Linear Regression Analysis and Sampling Theory Applications at McGill University. In recognition of his work, he was awarded the inaugural Jean-Claude Deville Prize by the French Statistical Society in 2022. His current research is funded by grants from the Natural Sciences and Engineering Research Council of Canada (NSERC) and Mitacs.
Department: Department of Medicine. Program: Experimental Medicine.