Yudan Wang (王钰丹) 

I am an research assistant professor in Department of Electrical and Computer Engineering, University of Central Florida.  I received my Ph.D. degree in May 2026 under the supervision of Prof. Shaofeng Zou. I received the M.S. from Univeristy at Buffalo, SUNY, under the supervision of Prof. Shaofeng Zou.  My B.S. in Mathematics from Sun Yat-sen University.  

My research interests specialize in machine learning, with a primary focus on reinforcement learning (RL). Below are some of the areas I am interested in:

• Theoretical and algorithmic foundations of reinforcement learning

• Multi-agent Reinforcement Learning

• Quantum in Reinforcement Learning

• [Sept. 2026] Our two papers are accepted by NeurIPS 2026. Thanks to all collaborators!

• [Apr. 2026] I passed my dissertation defense. Thanks for my advisor Prof. Shaofeng Zou and committee members!!

• [Feb. 2026] Our work Minimax Optimal Adversarial Reinforcement Learning is accepted by ICLR 2026. Thanks to the collaborators!

• Wang, Yudan, Kaiyi Ji, Ming Shi, and Shaofeng Zou. “Minimax Optimal Adversarial Reinforcement Learning.” International Conference on Learning Representations (ICLR 2026), 2026.

• Wang, Yudan, Peiyao Xiao, Hao Ban, Kaiyi Ji, and Shaofeng Zou. “Theoretical Study of Conflict-Avoidant Multi-Objective Reinforcement Learning.” IEEE Transactions on Information Theory, 2025.

• Wang, Yudan, Yue Wang, Yi Zhou, and Shaofeng Zou. “Non-Asymptotic Analysis for Single-Loop (Natural) Actor-Critic with Compatible Function Approximation. " Proceedings of the International Conference on Machine Learning (ICML 2024), 2024.

• Wang, Yudan, Shaofeng Zou, and Yue Wang. “Model-Free Robust Reinforcement Learning with Sample Complexity Analysis. ” Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI 2024), 2024.

• Wang, Yudan, Yue Wang, Yi Zhou, Alvaro Velasquez, and Shaofeng Zou. “Data-Driven Robust Multi-Agent Reinforcement Learning.” IEEE 32nd International Workshop on Machine Learning for Signal Processing (MLSP), 2022.