Biography

Runze Zhao

Bloomington, IN

woruozhao@gmail.com

Google Scholar · GitHub · CV

Runze Zhao

Randulf Zhao | 赵润泽

I am a third-year Computer Science Ph.D. student at Indiana University Bloomington, advised by Prof. Dongruo Zhou. I completed my Bachelor's degree in Financial Engineering at The Chinese University of Hong Kong, Shenzhen, advised by Prof. Wenye Li.

My research interests are in reinforcement learning, including:

Ongoing projects

  • Continuous Time Reinforcement Learning (CTRL)
  • Multi-Agent Reinforcement Learning (MARL)
  • Reinforcement Learning for LLMs
  • Reinforcement Learning for Agentic Frameworks

Published work

News

Oct 16, 2026I passed my Ph.D. qualifying exam! 🎉
May 01, 2026Our paper Instance-Dependent Continuous-Time Reinforcement Learning via Maximum Likelihood Estimation has been accepted to the International Conference on Machine Learning (ICML) 2026. 🎉 See you in July in Seoul, Korea.
May 07, 2025Our paper Sample and Computationally Efficient Continuous-Time Reinforcement Learning with General Function Approximation was accepted to UAI 2025. 🎉
Aug 01, 2024I started my Ph.D. journey at Indiana University Bloomington.

Selected Publications

ICML 2026

Instance-Dependent Continuous-Time Reinforcement Learning via Maximum Likelihood Estimation

Runze Zhao*, Yue Yu*, Ruhan Wang, Chunfeng Huang, Dongruo Zhou.

International Conference on Machine Learning, 2026.

Code PDF Poster

UAI 2025

Sample and Computationally Efficient Continuous-Time Reinforcement Learning with General Function Approximation

Runze Zhao*, Yue Yu*, Yiyue Zhu, Chen Yang, Dongruo Zhou.

Conference on Uncertainty in Artificial Intelligence, 2025.

Code PDF Poster

* Equal contribution.