About me

I am an Associate 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 information to be found in my resume

News:

• Jan 26: one paper accepted at Operations Research, on Blackwell and average optimality in robust Markov decision processes. This is joint work with Nicolas Vieille (HEC) and Marek Petrik (UNH).
• Oct 25: I am a recipient of an ANR grant (2026-2028) on uncertainty set selection in sequential decision-making problems, joint with Nian Si at HKUST.
• Oct 25: one paper accepted at the NeurIPS 2025 DynaFront workshop, with the best paper award!
• Sep 25: one paper accepted at NeurIPS 2025 (poster), on the interplay between mean-payoff and discounted stochastic games. This is joint work with Stephane Gaubert (CMAP, Ecole Polytechnique) and Ricardo Katz (CIFASIS-CONICET).
• Sep 25: I am now an associate professor at HEC!

Publications and preprints

Journals:

• Beyond discounted returns: Robust Markov decision processes with average and Blackwell optimality
  Julien Grand-Clément, Marek Petrik, Nicolas Vieille.
  Operations Research (accepted, 2026)
• On the convex formulations of robust Markov decision processes
  Julien Grand-Clément, Marek Petrik.
  Mathematics of Operations Research (2024), 50(3):1681-1706.
• The best decisions are not the best advice: Making adherence-aware recommendations
  Julien Grand-Clément, Jean Pauphilet.
  Management Science (2024), 72(1):667-692. The code for the simulations is available here.
• Solving optimization problems with Blackwell approachability
  Julien Grand-Clément, Christian Kroer.
  Mathematics of Operations Research (2023), 49(2):697-728. Slides are available here.
• Robustness of Proactive Intensive Care Units Transfer Policies
  Julien Grand-Clément, Carri Chan, Vineet Goyal, 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
  Elizabeth Chuang, Julien Grand-Clément, Jen-Ting Chen, Carri Chan, Vineet Goyal, 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
  Vineet Goyal, Julien Grand-Clément.
  Operations Research (2022), 71(2):517-535.
• Robust Markov Decision Process: Beyond Rectangularity
  Vineet Goyal, Julien Grand-Clément.
  Mathematics of Operations Research (2022), 48(1):203-226.
• The Operator Approach to Entropy Games
  Marianne Akian, Stéphane Gaubert, Julien Grand-Clément, Jérémie Guillaud.
  Theory of Computing Systems (2019) 63(5), 1089-1130. A preliminary version appeared in STACS 2017.

Refereed conferences:

• Thresholds for sensitive optimality and Blackwell optimality in stochastic games
  Stéphane Gaubert, Julien Grand-Clément, Ricardo D. Katz
  (NeurIPS 2025) 38th Advances in Neural Information Processing Systems.
• Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games
  Yang Cai, Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Weiqiang Zheng.
  (ICLR 2025)  International Conference on Learning Representations, 15th.
• Risk-averse Total-rewards MDPs with ERM and EVaR
  Xihong Su, Julien Grand-Clément, Marek Petrik.
  (AAAI 2025, oral) Proceedings of the AAAI Conference on Artificial Intelligence, 39th.
• Extensive-Form Game Solving Via Blackwell Approachability on Treeplexes
  Darshan Chakrabarti, Julien Grand-Clément, Christian Kroer.
  (NeurIPS 2024, spotlight) 38th Advances in Neural Information Processing Systems.
• Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms
  Yang Cai, Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Weiqiang Zheng.
  (NeurIPS 2024) 38th Advances in Neural Information Processing Systems. Some slides and the code for the experiments.
• Regret Matching+: (In)Stability and Fast Convergence in Games
  Gabriele Farina, Christian Kroer, Julien Grand-Clément, Chung-Wei Lee, Haipeng Luo.
  (NeurIPS 2023, spotlight) 37th Advances in Neural Information Processing Systems. The code for the simulations is available here. Some slides are available here.
• Reducing Blackwell and Average Optimality to Discounted MDPs via the Blackwell Discount Factor
  Julien Grand-Clément, Marek Petrik.
  (NeurIPS 2023) 37th Advances in Neural Information Processing Systems.
• Conic Blackwell Algorithm: Parameter-Free Convex-Concave Saddle-Point Solving
  Julien Grand-Clément, Christian Kroer.
  (NeurIPS 2021) 34th Advances in Neural Information Processing Systems.
• First-Order Methods for Wasserstein Distributionally Robust MDP
  Julien Grand-Clément, Christian Kroer.
  (ICML 2021) 38th International Conference on Machine Learning.
• Scalable First-Order Methods for Robust MDPs
  Julien Grand-Clément, Christian Kroer.
  (AAAI 2021) Proceedings of the AAAI Conference on Artificial Intelligence, 35(13), 12086-12094.

Refereed workshop at conferences:

• On the Separation Between Best-Iterate, Random-Iterate, and Last-Iterate Convergence of Learning in Games
  Y. Cai, G. Farina, J. Grand-Clément, C. Kroer, C.-W. Lee, H. Luo, W. Zheng
  (NeurIPS 2025) 39th Advances in Neural Information Processing Systems 
  Workshop: Dynamics at the Frontiers of Optimization, Sampling, and Games
  (Best paper award for the workshop)
• Optimality of stationary policies in risk-averse total-reward MDPs with EVaR
  X. Su, M. Petrik, J. Grand-Clément
  (ICML 2024) 41st International Conference on Machine Learning 
  Workshop: Foundations of Reinforcement Learning and Control

Working papers and preprints:

• Interpretable Machine Learning for Resource Allocation with Application to Ventilator Triage
  Julien Grand-Clément, You-Hui Goh, Carri Chan, Elizabeth Chuang, Vineet Goyal.
  Preliminary version accepted at the American Thoracic Society 2021 International Conference.
• Tractable Markov Decision Processes
  Julien Grand-Clément, Nian Si, Shengbo Wang.
• On the Separation Between Best-Iterate, Random-Iterate and Last-Iterate Convergence of Learning in Games
  Yang Cai, Gabriele Farina, Julien Grand-Clément, Christian Kroer, Chung-Wei Lee, Haipeng Luo, Weiqiang Zheng.
  A preliminary version of this paper won the best paper award at the DynaFront Workshop at NeurIPS 2025.
• Playing against a stationary adversary
  Julien Grand-Clément, Nicolas Vieille

Technical report:

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

Teaching

• HEC Paris, 2021 - present:
  • Introduction to Data Science, graduate core course (~ 200 students)
  • Operations and Supply Chain Management, graduate core course (~ 300 students)
  • Sustainable Operations and Supply Chain Management, undergraduate core course (~ 140 students)
  • Sustainable Artificial Intelligence, undergraduate core course (~ 400 students)
  • Artificial Intelligence and Climate Change, certificate course (~ 50 students). Slides available here.
  • Les grands défis de l'IA, undergraduate (~ 50 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).