Anran Hu

Anran Hu

Anran Hu works at the intersection of stochastic control, game theory, optimization, and machine learning. Her primary research areas include mean-field games, continuous-time stochastic control, and reinforcement learning. She is also interested in FinTech and the application of machine learning and reinforcement learning to finance.

A significant focus of Hu's research is the reinforcement learning of large-population games and continuous-time stochastic control systems. Additionally, she works on developing optimization formulations and novel modeling generalizations of mean-field games and their extensions. Her research encompasses new theoretical frameworks, analytical methods, efficient algorithms, and open-source software. These contributions have broad applications in finance, economics, transportation, robotics, and energy systems.

Before joining Columbia University, Hu was a Hooke Research Fellow at the Mathematical Institute, University of Oxford. She completed her Ph.D. in Industrial Engineering and Operations Research (IEOR) at UC Berkeley, advised by Prof. Xin Guo. Prior to Berkeley, she earned her B.S. degree from the School of Mathematical Sciences at Peking University.