I am a fourth year Ph.D. student at Tsinghua-Berkey Shenzhen Institute (TBSI) of Tsinghua Unviversity, advised by Prof. Wenbo Ding. I originally joined TBSI as a master’s student and, after three years of research (2021-2024), transitioned to the Ph.D. track. I received the B.Eng degree in communication engineering in Chien-Shiung Wu College from Southeast University, Nanjing, China, in 2021.

My research interest includes Reinforcement Learning, Multi-Agent System and Large Models. My current work focuses on advanced topics in reinforcement learning, decision systems, and complex adaptive systems, with an emphasis on applications that bridge theory and practice.

I’m passionate about solving real-world challenges through interdisciplinary research, and my academic journey has been shaped by a desire to push the boundaries of intelligent systems. Outside of my core research, I have a growing interest in fostering collaboration across fields to address high-dimensional problems and system-level optimization.

Feel free to explore my work, and I look forward to connecting with fellow researchers and collaborators!

Contact

Email: thz21@mails.tsinghua.edu.cn; tanghz24@mails.tsinghua.edu.cn; / Github: Huaze Tang’s main page; / Wechat: QR code

News

• [2025/01] Our paper Residual Kernel Policy Network: Enhancing Stability and Robustness in RKHS-Based Reinforcement Learning gets accepted as poster in ICLR 2025! See you in Singapore!
• [2025/01] Our paper Mean-Field Aided QMIX: A Scalable and Flexible Q-Learning Approach For Large-Scale Agent Groups gets accepted in ICASSP 2025. See you in Hyderabad!
• [2024/08] Transitioned to the Ph.D. track.
• [2024/04] Present my work M^3ARL: Moment-Embedded Mean-Field Multi-Agent Reinforcement Learning for Continuous Action Space at ICASSP 2024.
• [2024/01] Start research internship in Meituan.