Sébastien Le Digabel
Member, GERAD

Professor, Department of Mathematics and Industrial Engineering, Polytechnique Montréal
Biography
Sébastien Le Digabel is a Professor of Mathematics at Polytechnique Montreal and a regular member of the GERAD research center. Before that, he obtained a PhD in applied mathematics from Polytechnique in 2008, and worked as a postdoctoral fellow at the IBM Watson Research Center and the University of Chicago in 2010 and 2011.
His research interests include the analysis and development of algorithms for blackbox optimization, and the design of related software. Blackbox optimization occurs when the functions to optimize are given by numerical simulations for which derivative information is not available. In this context, derivative-free optimization may be considered, and in particular the Mesh Adaptive Direct Search (MADS) method of Audet and Dennis, for which Le Digabel's thesis brought some extensions and upgrades. All of his work on MADS is included in the NOMAD software, a free package for blackbox optimization available at www.gerad.ca/nomad.
S. Le Digabel's research is funded by the Canadian NSERC foundation, the Quebec FRQNT fund, IVADO, InnovÉÉ, Hydro-Québec, Rio Tinto, and Huawei-Canada.
Education
Research Axes
Research Applications
Publications
News
Congratulations to Nathan Allaire, PhD student at Polytechnique Montréal. He was awarded the the Best Industrial Paper Award during the 14th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2025) held in Porto, Portugal.
Title: Répartition computationelle efficace entre boîte noire et solveur
GERAD is pleased to award 4 scholarships for foreign interns who will come to work in our offices this summer.
Events
Sébastien Le Digabel – Professor, Department of Mathematics and Industrial Engineering, Polytechnique Montréal
Miguel F. Anjos – Professor, School of Mathematics, University of Edinburgh
Nicolau Andres Thio – The University of Melbourne
Prizes and awards
Best Industrial Paper Award
"Zeroth Order Optimization for Pretraining Language Models" is authored by Nathan Allaire, Mahsa Ghazvini Nejad, Sébastien Le Digabel and Vahid Partovi NiaProfessor among the world’s most influential researchers in 2020
Professor among the world’s most influential researchers in 2019
First prize in the 2019 CORS Student Paper Competition
"Tight-and-Cheap Conic Relaxation for the AC Optimal Power Flow Problem" (with M.F. Anjos and C. Bingane)Software
Editorial Boards & Comittees
Associate Editor
- OMS: Optimization Methods and Software, 12/2024-...
- JOTA: Journal of Optimization Theory and Applications, 2021-...
- INFOR: Information Systems and Operational Research, 2017-...
Guest Editor
- Special issue in JOGO , "Derivative-free and Blackbox Optimization", 2024-2025
- Special issue in JOGO for the 40th anniversary of GERAD, 2018-2019
- Special issue in INFOR for the EUROPT 2017 conference, 2017-2019