Laurent Charlin

Lab Scientist - Machine Learning

Type: Scientist

Site: Montreal

Stream: Artificial Intelligence, Supply Chain

Laurent is an assistant professor in the department of decision sciences at HEC (and adjunct at the DIRO). He develops novel machine learning models, particularly probabilistic graphical models, to help in decision making. His recent work has focused on extending the capabilities of recommender systems. He is generally interested in applying learning methods to analyze different data. Laurent has co-developed the Toronto Paper Matching System (TPMS) which is a tool to assist conference organizers match their reviewers to submitted papers. The system is now online and has been used by large machine learning and computer vision conferences over the last few years. He graduated with a PhD from the University of Toronto where he worked with Rich Zemel and Craig Boutilier. He also has a Master’s from U. Waterloo where he was supervised by Pascal Poupart. Finally, Laurent did postdocs at Princeton and Columbia under the supervision of David Blei and at McGill with Joelle Pineau.