I am a visiting assistant professor/faculty fellow in the computer science department at the Courant Institute at New York University, working with Prof. Georg Stadler. Previously, I was a postdoctoral research associate in the Division of Applied Mathematics at Brown University.
My research focuses on optimization, scientific computing, statistics and partial differential equations. My Ph.D. dissertation, completed under the supervision of Prof. Jérôme Darbon, focused on developing efficient and robust optimization algorithms for large-scale supervised learning tasks (e.g., regression and classification in machine learning) and investigating connections between Hamilton–Jacobi PDEs and both machine learning and imaging science.
Before my doctoral studies, I completed my M.Sc. degree in applied mathematics in 2015 from ETH Zürich with Prof. George Haller as my M.Sc. thesis advisor. I completed my B.Sc. degree in applied mathematics and physics in 2013 from McGill University with Prof. Michael C. Mackey as my undergraduate honors thesis advisor.
Gabriel Provencher Langlois
Courant Institute of Mathematical Sciences
New York University
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New York City, NY, 10012