Invited Talks

Tuesday 11 November, 10:30am

Louis-Martin Rousseau: Towards neuro-symbolic CP

This presentation explores the integration of machine learning into constraint programming (CP) to build the next generation of neuro-symbolic solvers. It highlights how learning-based techniques—such as reinforcement learning and graph neural networks—can enhance search heuristics and propagation strategies. The presentation also examines recent advances in leveraging Lagrangian relaxation and decomposition methods through learning to strengthen dual bounds and improve solver efficiency. Finally, it explores how AI can be used to enhance the art of modelling in CP, and it discusses the many challenges of combining artificial intelligence and logical reasoning to enhance the power, adaptability, and scalability of combinatorial optimization.

Louis-Martin Rousseau is a Professor in the Department of Mathematics and Industrial Engineering at Polytechnique Montréal. An internationally recognized expert in artificial intelligence, operations research, and management science, his work focuses on combinatorial optimization, column generation, transportation logistics, scheduling, and healthcare resource optimization. Since 2016, he has held the Canada Research Chair in Healthcare Logistics (HANALOG), where his research aims to improve the planning and efficiency of healthcare services through advanced optimization and AI-driven decision-support systems.

Wednesday 12 November, 9:00am (joint with ICAPS)

Hanna Kurniawati

Details coming soon

Thursday 13 November, 9:00am (joint with ICAPS)

Bistra Dilkina

Details coming soon