Publications

Articles de journal

1. Vincent Mai, Philippe Maisonneuve, Tianyu Zhang, Hadi Nekoei, Liam Paull, and Antoine Lesage-Landry. "Multi-agent Reinforcement Learning for Fast-Timescale Demand Response of Residential Loads," Machine Learning. Under review. March 2023. (arXiv)
2. Antoine Lesage-Landry, Félix Pellerin, Duncan S. Callaway, and Joshua A. Taylor. "Optimally Scheduling Public Safety Power Shutoffs," INFORMS Stochastic Systems. Accepted. May 2023. (arXiv)
3. Antoine Lesage-Landry and Duncan S. Callaway. "Approximated Multi-Agent Fitted Q-Iteration," Systems & Control Letters, 177: 105563. July 2023. (doi)
4. Feng Li, Ilhan Kocar, and Antoine Lesage-Landry. "A Rapid Method for Impact Analysis of Grid-edge Technologies on Power Distribution Networks," IEEE Transactions on Power Systems. March 2023. (doi)
5. Jean-Luc Lupien and Antoine Lesage-Landry. "An Online Newton's Method with Linear Time-varying Equality Constraints," IEEE Control Systems Letters, 6: 1423-1428. February 2023. (doi)
6. Antoine Lesage-Landry, Joshua A. Taylor, and Duncan S. Callaway. "Online Convex Optimization with Binary Constraints," IEEE Transactions on Automatic Control, 66 (12): 6164-6170. December 2021. (doi)
7. Antoine Lesage-Landry and Duncan S. Callaway. "Batch Reinforcement Learning for Network-Safe Demand Response in Unknown Electric Grids," Electric Power Systems Research, 202: 108375. November 2022. (doi)
8. Antoine Lesage-Landry, Joshua A. Taylor, and Iman Shames. "Second-order Online Nonconvex Optimization," IEEE Transactions on Automatic Control, 66 (10): 4866-4872. October 2021. (doi)
9. Antoine Lesage-Landry, Han Wang, Iman Shames, Pierluigi Mancarella, and Joshua A. Taylor. "Online Convex Optimization of Multi-energy Building-to-grid Ancillary Services," IEEE Transactions on Control Systems Technology, 28 (6): 2416 - 2431. November 2020. (doi)
10. Antoine Lesage-Landry and Duncan S. Callaway. "Dynamic and Distributed Online Convex Optimization for Demand Response of Commercial Buildings," IEEE Control Systems Letters, 4 (3): 632-637. July 2020. (doi)
11. Antoine Lesage-Landry, Siyu Chen, and Joshua A. Taylor. "Estimating the Frequency Coupling Matrix from Network Measurements," IEEE Transactions on Control of Network Systems, 7 (2): 724-733. June 2020. (doi)
12. Antoine Lesage-Landry, Iman Shames, and Joshua A. Taylor. "Predictive Online Convex Optimization," Automatica, 113: 108771, March 2020. (doi)
13. Antoine Lesage-Landry and Joshua A. Taylor. "A Second-order Cone Model of Transmission Planning with Alternating and Direct Current Lines," European Journal of Operational Research, 281 (1): 174-185. February 2020. (doi)
14. Olivier Ouellette, Antoine Lesage-Landry, Benjamin Scheffel, Sjoerd Hoogland, F. Pelayo Garcia de Arquer, and Edward H. Sargent. "Spatial Collection in Colloidal Quantum Dot Solar Cells," Advanced Functional Materials, 3 (1): 1908200. January 2020. (doi)
15. Antoine Lesage-Landry and Joshua A. Taylor. "Setpoint Tracking with Partially Observed Loads." IEEE Transactions on Power Systems, 32 (5): 5615-5627. September 2018. (doi)
16. Antoine Lesage-Landry and Joshua A. Taylor. "The Multi-armed Bandit with Stochastic Plays," IEEE Transactions on Automatic Control, 63 (7): 2280-2286. July 2018. (doi)

Articles de conférence

1. Feng Li, Ilhan Kocar, and Antoine Lesage-Landry. "Mitigating Equipment Overloads due to Electric Vehicle Charging Using Customer Incentives," 2023 IEEE Power & Energy Society General Meeting. Accepted. March 2023. (doi)
2. Vincent Mai, Philippe Maisonneuve, Tianyu Zhang, Hadi Nekoei, Liam Paull, and Antoine Lesage-Landry. "Multi-agent Reinforcement Learning for Fast-Timescale Demand Response of Residential Loads," 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS). May 2023.
3. Vincent Mai, Philippe Maisonneuve, Tianyu Zhang, Jorge Montalvo, Liam Paull, and Antoine Lesage-Landry. "Multi-agent Reinforcement Learning for Fast-Timescale Demand Response," Reinforcement Learning for Real Life Workshop @ NeurIPS 2022. December 2022. (pdf)
4. Vincent Mai, Tianyu Zhang, and Antoine Lesage-Landry. "Multi-agent Reinforcement Learning for Renewable Integration in the Electric Power Grid," Tackling Climate Change with Machine Learning: workshop at NeurIPS 2021, online, December 2021. (pdf)
5. Antoine Lesage-Landry and Duncan S. Callaway. "Batch Reinforcement Learning for Network-Safe Demand Response in Unknown Electric Grids," 22nd Power Systems Computation Conference (PSCC 2022), February 2022. (doi)
6. Rodrigo Henriquez, Antoine Lesage-Landry, Joshua A. Taylor, Daniel Olivares, and Matias Negrete-Pincetic. "Managing Load Contract Restrictions with Online Learning," , IEEE Global Conference on Signal and Information Processing (GlobalSIP), November 2017. (doi)
7. Amr Mohamed, Antoine Lesage-Landry, and Joshua A. Taylor. "Dispatching Thermostatically Controlled Loads for Frequency Regulation Using Adversarial Multi-armed Bandits," 2017 IEEE Electrical Power and Energy Conference (EPEC), October 2017. (doi)
8. Antoine Lesage-Landry and Joshua A. Taylor. "Online Convex Optimization for Demand Response," X Bulk Power Systems Dynamics and Control Symposium, IREP’2017 Symposium., August 2017. (pdf)
9. Antoine Lesage-Landry and Joshua A. Taylor. "Learning to Shift Thermostatically Controlled Loads," Proceedings of the 50th Hawaii International Conference on System Sciences, January 2017. (doi)
10. Sébastien Loranger, Antoine Lesage-Landry, Elton Soares de Lima Filho, Galina Nemova, Noelio O. Dantas, Paulo C. Morais, and Raman Kashyap. "Spectroscopic and life-time measurements of quantum dot doped glass for optical refrigeration: A feasibility study," SPIE OPTO. International Society for Optics and Photonics, February 2013. (doi)

Séminaires et présentations

• Analyzing and Mitigating Impacts of Grid-edge Technologies on Power Distribution Networks. University of Toronto: ECE Seminar, Toronto, ON. February 2023.
• Optimally Scheduling Public Safety Power Shutoffs. University of Michigan: Michigan Power and Energy Laboratory Seminar, Ann Arbor, MI. February 2023.
• A Rapid Method for Impact Analysis of Grid-edge Technologies on Power Distribution Networks. Resilient Electric Grid Consortium of North America Symposium 2022 (RECONS 2022), College Station, TX. November 2022.
• Optimally Scheduling Public Safety Power Shutoffs. Northwestern University: Department of Electrical and Computer Engineering Seminar Series, Evanston, IL. October 2022.
• Optimally Scheduling Public Safety Power Shutoffs. University of British Columbia: ECE Seminar, Vancouver, BC. June 2022.
• Optimally Scheduling Public Safety Power Shutoffs. Northeastern University: MIE Seminar Series, Boston, MA. May 2022.
• Batch Reinforcement Learning for Network-Safe Demand Response. ETH Zürich: Power Systems Laboratory Seminar, Zürich, Switzerland/online. March 2022.
• Real-time Decision-making for Demand Response. University of California, San Diego: Joint Mechanical & Aerospace Engineering Department and Center for Energy Research, San Diego CA/online. November 2021.
• Fitted Q-Iteration for Network-Safe Demand Response. 2021 INFORMS Annual Meeting, Anaheim, CA/online. October 2021. Invited.
• Real-Time Decision-making for Demand Response Under Uncertainty. GERAD Webinar. Montréal, QC, online. March 2021.
• Dynamic and Distributed Online Convex Optimization for Demand Response of Commercial Buildings. 59^th IEEE Conference on Decision and Control (CDC), online. December 2020.
• Online Convex Optimization with Binary Constraints for Demand Response. 2020 INFORMS Annual Meeting, online. November 2020. Invited.
• Predictive Online Convex Optimization for Demand Response. 2019 INFORMS Annual Meeting, Seattle, WA. October 2019. Invited.
• A Second-order Cone Model of AC-DC Transmission Expansion Planning. Canadian Operational Research Society 61^st Annual Conference, Saskatoon, SK. May 2019.
• Online Convex Optimization for Demand Response in Power Systems. Conference on Information Sciences and Systems, Johns Hopkins University. Baltimore, MD, March 2019. Invited.
• Renewable Integration and Demand Response. ECE1476 - LEDs and Solar Cells, University of Toronto, Toronto, ON. November 2018.
• Online Learning for Demand Response. The University of Melbourne: Electrical and Electronic Engineering Seminar, Melbourne, VIC, Australia. February 2018.
• Estimation du mouvement de tumeur pulmonaire: un modèle basé sur des images diagnostiques 3D. Student Conference of the Clinical Medical Physicists Association of Québec. Québec City, QC. November 2014.