Scholar
Maxime Heuillet
Google Scholar ID: SduUuGQAAAAJ
PhD candidate, Université Laval, Mila
Citations & Impact
Citations
21
H-index
2
i10-index
1
Publications
8
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- Selected publications: 'Randomized Confidence Bounds for Stochastic Partial Monitoring', ICML Main Track, 2024; 'Neural Active Learning Meets the Partial Monitoring Framework', UAI Main Track, 2024. Workshop publications at NeurIPS, ICML, AAAI, etc.
Research Experience
- Interned at Thales (CortAIx lab), Noah's Ark lab, and Amazon in Seattle.
Education
- Ph.D. Candidate in Computer Science, Université Laval & MILA – Québec AI Institute, Advisor: Audrey Durand; M.Sc. from the National School of Statistics and Data Analysis (ENSAI) in France.
Background
- Research interests include interactive learning (such as bandits, partial monitoring, active learning, gflownets), reinforcement learning, robustness, efficiency, large language models, recommender systems, and automated machine learning. Focused on building efficient, robust, and generalizable ML systems.
Miscellany
- Contact: maxime[.]heuillet1[at]ulaval.ca
Co-authors