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Pascal Germain is a professor in computer science and a researcher in machine learning. After obtaining his PhD in computer science from Laval University in 2015, under the supervision of François Laviolette and Mario Marchand, he continued his research in France for four years at Inria (the national institute dedicated to digital sciences), first as a postdoctoral researcher and then as a research officer. He was also an affiliated member and lecturer in the mathematics department at the University of Lille. Returning to his alma mater as a professor in 2019, he teaches programming and continues his work on the statistical theory of machine learning, transfer learning of representations, and interpretable predictor learning. His main scientific contributions focus on PAC-Bayesian theory and domain adaptation.
Inria Paris • France
Conducted research in machine learning.
Inria Lille - Nord Europe • France
Conducted research on machine learning.
Laval University • Québec, Canada
Teaches programming and conducts machine learning research.
Department of Management / MBA programs often require higher GPAs and specific English proficiency.