Antoine Lesage-Landry
B.Eng. (Poly), Ph.D. (Toronto)
Assistant Professor
Department of Electrical Engineering
Department of Electrical Engineering
Research interests and affiliations
Research interests
- Modeling of power systems
- Decision-making under uncertainty
- Optimization
- Online optimization
- Online learning
- Machine learning
- Electric energy systems
- Renewable energy systems
- Smart grids
Affiliation(s)
- Réseau québécois sur l'énergie intelligente, Member
- Research Group in Decision Analysis (GERAD), Member
- Institute for Data Valorization (IVADO), Member
- Mila - Quebec's Artificial Intelligence Institute, Associate member
Expertise type(s) (NSERC subjects)
- 2501 Power systems
- 2715 Optimization
- 2805 Learning and inference theories
- 2956 Optimization and optimal control theory
- 2960 Mathematical modelling
Publications
Recent publications
Journal article
Journal article
Conference paper
Journal article
Lesage-Landry, A. & Callaway, D.S. (2022). Batch reinforcement learning for network-safe demand response in unknown electric grids. Electric Power Systems Research, 212, 7 pages. Retrieved from https://doi.org/10.1016/j.epsr.2022.108375
Li, F., Kocar, I. & Lesage-Landry, A. (2022). Rapid method for impact analysis of grid-edge technologies on power distribution networks. Cahier du Gerad, 2022-45, 20 pages. Retrieved from https://www.gerad.ca/en/papers/G-2022-45
Mai, V., Zhang, T. & Lesage-Landry, A. (2021). Multi-agent reinforcement learning for renewable integration in the electric power grid. Paper presented at the NeurIPS Workshop on Tackling Climate with Machine Learning.
Lesage-Landry, A., Taylor, J.A. & Callaway, D.S. (2021). Online convex optimization with binary constraints. IEEE Transactions on Automatic Control, 66(12), 6164-6170. Retrieved from https://doi.org/10.1109/TAC.2021.3061625
See all publications (18)
Biography
Antoine Lesage-Landry is an Assistant Professor in the Department of Electrical Engineering at Polytechnique Montréal, QC, Canada. He received the B.Eng. degree in Engineering Physics from Polytechnique Montréal, in 2015, and the Ph.D. degree in Electrical Engineering from the University of Toronto, ON, Canada, in 2019. From 2019 to 2020, he was a Postdoctoral Scholar in the Energy & Resources Group at the University of California, Berkeley, CA, USA. His research interests include optimization, online learning, and their application to power systems with renewable generation.
Education
- Ph.D., Electrical Engineering, University of Toronto
- B.Eng., Engineering Physics, Polytechnique Montréal