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Quentin Cappart
B.Sc., M.Sc., Ph.D. (Université catholique de Louvain, Louvain, Belgium)

Research interests and affiliations

Research interests
  • Combinatorial optimization
  • Reinforcement learning
  • Constraint programming
  • Search algorithms
  • Mathematical modeling
  • Operations research
  • Machine learning
Expertise type(s) (NSERC subjects)
  • 1601 Operations research and management science
  • 2713 Algorithms
  • 2715 Optimization
  • 2800 ARTIFICIAL INTELLIGENCE (Computer Vision, use 2603)
  • 2960 Mathematical modelling

Publications

Recent publications
Journal article
Cappart, Q., Bergman, D., Rousseau, L.-M., Premont-Schwarz, I. & Parjadis, A. (2022). Improving variable orderings of approximate decision diagrams using reinforcement learning. INFORMS Journal on Computing, 19 pages. Retrieved from https://doi.org/10.1287/ijoc.2022.1194
Journal article
Joshi, C.K., Cappart, Q., Rousseau, L.-M. & Laurent, T. (2022). Learning the travelling salesperson problem requires rethinking generalization. Constraints, 27(1-2), 70-98. Retrieved from https://doi.org/10.1007/s10601-022-09327-y
Conference paper
Cappart, Q., Moisan, T., Rousseau, L.M., Premont-Schwarz, I. & Cire, A.A. (2021). Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization. Paper presented at the 35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence (pp. 3677-3687). Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/16484/16291
Journal article
Kafaei, P., Cappart, Q., Renaud, M.-A., Chapados, N. & Rousseau, L.M. (2021). Graph neural networks and deep reinforcement learning for simultaneous beam orientation and trajectory optimization of Cyberknife. Physics in Medicine and Biology, 66(21), 17 pages. Retrieved from https://doi.org/10.1088/1361-6560/ac2bb5

Biography

Quentin Cappart is an assistant professor at the Department of Computer and Software Engineering of Polytechnique Montréal. He obtained a B.Sc. in engineering (2012), a M.Sc. in computer engineering (2014), a M.Sc. in management (2018), and a Ph.D. (2017) at the Université catholique de Louvain (Belgium). After his Ph.D, he joined Polytechnique Montréal and CIRRELT as a postdoctoral fellow from 2018 to 2020. During these two years, he was also a research intern at ElementAI and worked in the integration of machine learning and operations research.

Education

  • Bachelor in engineering, Université catholique de Louvain
  • Master in computer engineering, Université catholique de Louvain
  • Master in management, Université catholique de Louvain
  • Ph.D. in engineering sciences, Université catholique de Louvain

Supervision at Polytechnique

COMPLETED

  • Master's Thesis (1)

    • Omrani, B. (2021). Apprentissage par renforcement d'heuristiques de branchement en programmation par contraintes (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/6571/