Julien Grand-Clément

I am an Assistant Professor in the Information Systems and Operations Management department at HEC Paris, and a Hi! Paris chair holder. My research focuses on data-driven decision making under parameter uncertainty, with applications in healthcare and algorithmic game theory. I received my Ph.D. in Operations Research from Columbia University in 2021 where my advisors were Prof. Vineet Goyal and Prof. Carri Chan. Before Columbia, I completed my master and undergraduate studies at Ecole polytechnique (France) in 2016, with a major in algorithms and optimization.

Info: Google Scholar / resume

Contact: grand-clement@hec.fr

News: My paper on making adherence-aware recommendations has been accepted to Management Science, special issue on human-AI connections. This is joint work with Jean Pauphilet (LBS).

Publications and preprints

Journals:

• The best decisions are not the best advice: Making adherence-aware recommendations
  joint with Jean Pauphilet.
  Management Science (2023, forthcoming).
• Solving optimization problems with Blackwell approachability
  joint with Christian Kroer.
  Mathematics of Operations Research (2023, forthcoming). Slides are available here.
• Robustness of Proactive Intensive Care Units Transfer Policies
  joint with Carri Chan, Vineet Goyal, and Gabriel Escobar.
  Operations Research (2022) 71(5):1653-1688. The code for the simulations is available here.
• Quantifying Utilitarian Outcomes to Inform Triage Ethics: Simulated Performance of a Ventilator Triage Protocol Under SARS-CoV-2 Pandemic Surge Conditions
  joint with Elizabeth Chuang, Jen-Ting Chen, Carri Chan, Vineet Goyal and Michelle Ng Gong.
  American Journal of Bioethics – Empirical Bioethics (2022), vol. 13, no 3, p. 196-204.
• A First-Order Approach to Accelerated Value Iteration
  joint with Vineet Goyal.
  Operations Research (2022), 71(2):517-535.
• Robust Markov Decision Process: Beyond Rectangularity
  joint with Vineet Goyal.
  Mathematics of Operations Research (2022), 48(1):203-226.
• The Operator Approach to Entropy Games
  joint with Stéphane Gaubert, Marianne Akian, and Jérémie Guillaud.
  Theory of Computing Systems (2019) 63(5), 1089-1130. A preliminary version appeared in STACS 2017.

Refereed conferences:

• Regret Matching+: (In)Stability and Fast Convergence in Games
  joint with Gabriele Farina, Christian Kroer, Chung-Wei Lee and Haipeng Luo.
  (NeurIPS 2023, spotlight) 36th Advances in Neural Information Processing Systems.
• Reducing Blackwell and Average Optimality to Discounted MDPs via the Blackwell Discount Factor
  joint with Marek Petrik.
  (NeurIPS 2023) 36th Advances in Neural Information Processing Systems.
• Conic Blackwell Algorithm: Parameter-Free Convex-Concave Saddle-Point Solving
  joint with Christian Kroer.
  (NeurIPS 2021) Proceedings of the 34th Advances in Neural Information Processing Systems, 34:9587-9599 , 2021.
• First-Order Methods for Wasserstein Distributionally Robust MDP
  joint with Christian Kroer.
  (ICML 2021) Proceedings of the 38th International Conference on Machine Learning, PMLR 139:2010-2019, 2021.
• Scalable First-Order Methods for Robust MDPs
  joint with Christian Kroer.
  (AAAI 2021) Proceedings of the AAAI Conference on Artificial Intelligence, 35(13), 12086-12094.

Working papers:

• Interpretable Machine Learning for Resource Allocation with Application to Ventilator Triage
  joint with Carri Chan, Elizabeth Chuang and Vineet Goyal.
  Preliminary version accepted at the American Thoracic Society 2021 International Conference.
  
  

• The Best Decisions Are Not the Best Advice: Making Adherence-Aware Recommendations
  joint with Jean Pauphilet.

• On the convex formulations of robust Markov decision processes
  joint with Marek Petrik.

• Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games
  joint with Yang Cai, Gabriele Farina, Christian Kroer, Chung-Wei Lee, Haipeng Luo and Weiqiang Zheng.

Technical report:

• From Convex Optimization to MDPs: A Review of First-Order, Second-Order and Quasi-Newton Methods for MDPs.

Teaching

• HEC Paris, 2021 - present:
  • Operations and Supply Chain Management, graduate core course (~ 200 students)
  • Sustainable Operations and Supply Chain Management, undergraduate core course (~ 140 students)

• Columbia University, 2016 - 2021, undergraduate & graduate courses (~ 450 students).
  • Convex Optimization (IEOR 6616).
  • Advanced Optimization (IEOR 4004).
  • Foundations of Optimization (IEOR 3608).
  • Dynamic Pricing & Revenue Management (IEOR 4601).
  • Game Theoretic Models of Operations (IEOR 4407).
  • Operations Management (IEOR 4000).

• Mathematics Oral Examiner, Lycee Saint-Louis, Spring 2015, undergraduate level (~ 40 students).