Haotian Gu

Department of Mathematics, UC Berkeley

About Me

Hi! I am a fifth-year Ph.D. candidate in applied mathematics at UC Berkeley. I am jointly advised by Prof. Xin Guo and Prof. Fraydoun Rezakhanlou. Before entering UC Berkeley, I completed my Bachelor degree in mathematics at the University of Hong Kong.

My research focuses on the intersection of stochastic control, game theory and reinforcement learning. Meanwhile, I also work on theoretical machine learning regarding robustness and transferability.

Google Scholar---LinkedIn---Resume---Email


Mean-field Control and Reinforcement Learning

  • Dynamic programming principles for learning Mean-field controls [arXiv]

    • Haotian Gu, Xin Guo, Xiaoli Wei, Renyuan Xu.

    • Accepted by Operation Research.

  • Q-Learning for Mean-Field Controls with Convergence and Complexity Analysis [arXiv]

    • Haotian Gu, Xin Guo, Xiaoli Wei, Renyuan Xu.

    • Accepted by SIAM Journal on Mathematics of Data Science.

    • Short Version accepted by Workshop on Theoretical Foundations of Reinforcement Learning, ICML 2020.

  • Mean-Field Multi-Agent Reinforcement Learning: A Decentralized Network Approach [arXiv]

    • Haotian Gu, Xin Guo, Xiaoli Wei, Renyuan Xu.

    • Submitted to Mathematics of Operation Research.

Adversarial Robustness

  • An SDE Framework for Adversarial Training, with Convergence and Robustness Analysis [arXiv]

    • Haotian Gu, Xin Guo, Xinyu Li

Federated Learning

  • BoFL: Bayesian Optimized Local Training Pace Control for Energy Efficient Federated Learning

    • Hongpeng Guo, Haotian Gu, Zhe Yang, Xiaoyang Wang, Eun Kung Lee, Nandhini Chandramoorthy, Tamar Eilam, Deming Chen, Klara Nahrstedt.

    • Accepted by the 23rd ACM/IFIP International Middleware Conference.

Management Science

  • Relay Freight Index: Freight Market Rate Prediction with Signature Transform

    • Haotian Gu, Xin Guo, Tim Jacobs, Philip Kaminsky

    • Available upon request

PDE and Numerical Analysis

  • An Efficient Model Reduction Method for Solving Viscous G-equations in Incompressible Cellular Flows [arXiv]

    • Haotian Gu, Jack Xin, Zhiwen Zhang.

    • Accepted by SIAM Journal on Scientific Computing.

  • Analysis on Hybrid Fractals [arXiv]

    • Patricia Alonso-Ruiz, Yuming Chen, Haotian Gu, Robert Strichartz, Ziri Zhou.

    • Accepted by Communications on Pure and Applied Analysis

Invited Talks

  • Numerical Analysis Seminar: April 2022, University of Hong Kong, Virtual Conference

  • Student Probability/PDE Seminar: April 2021, University of California, Berkeley

  • Workshop on the Intersection of Machine Learning, Control and Games: November 2020, INFORMS Annual Meeting 2020, Virtual Conference

  • Workshop on Theoretical Foundations of Reinforcement Learning: July 2020, International Conference on Machine Learning 2020, Virtual Conference

  • Seminar on Applied Mathematics: May 2018, University of Hong Kong, Pok Fu Lam

  • Cornell Conference on Analysis, Probability, and Mathematical Physics on Fractals: June 2017, Cornell University, Ithaca

Teaching Experience

  • MATH 170 Mathematical Methods for Optimization: Fall 2020, teaching assistant for Prof. Lawrence Evans

  • MATH 195 Calculus of Variations and Optimal Control: Spring 2021, teaching assistant for Prof. Lawrence Evans

  • IEOR 222 Financial Engineering Systems: Spring 2022, teaching assistant for Prof. Thibaut Mastrolia

Industry Experience

Research Scientist Intern, Amazon

  • Remote, May 2021 - August 2021

  • Middle Mile Planning, Research & Optimization Sciences

Quantitative Research Intern, Citadel Securities

  • Chicago, June 2022 - August 2022

  • Systematic FICC