Mathieu Laurière

Mathieu Laurière is an Assistant Professor of Mathematics and Data Science at NYU Shanghai. Prior to joining NYU Shanghai, he was a Postdoctoral Research Associate at Princeton University in the Operations Research and Financial Engineering (ORFE) department, and a Visiting Faculty Researcher at Google Brain. He obtained his MS from Sorbonne University and ENS Paris-Saclay and his PhD from the University of Paris. Before joining Princeton University, he was a Postdoctoral Fellow at the NYU-ECNU Institute of Mathematical Sciences at NYU Shanghai.

Selected Publications

• Dayanikli, G., & Lauriere, M. (2025). A machine learning method for Stackelberg mean field games. Mathematics of Operations Research.
• Cao, H., Guo, X., & Laurière, M. (2024). Connecting GANs, mean-field games, and optimal transport. SIAM Journal on Applied Mathematics, 84(4), 1255-1287.
• Ramponi, G., Kolev, P., Pietquin, O., He, N., Laurière, M., & Geist, M. (2024). On imitation in mean-field games. Advances in Neural Information Processing Systems, 36.
• Carmona, R., Laurière, M., & Tan, Z. (2023). Model-free mean-field reinforcement learning: mean-field MDP and mean-field Q-learning. The Annals of Applied Probability, 33(6B), 5334-5381.
• Achdou, Y., Lauriere, M., & Lions, P. L. (2021). Optimal control of conditioned processes with feedback controls. Journal de Mathématiques Pures et Appliquées, 148, 308-341.