Yuanji Zou

I’m a Ph.D. candidate at University of Minnesota, advised by Dr. Elia with the Department of Electrical and Computer Engineering. My research focus on the Multi-agent Reinforcement Learning problems and Partially Observable Markov Decision Process. I’m interested in how model-based reinforcement learning techniques—and the resulting policies—can significantly enhance the performance of multi-agent systems, with potential applications in large-scale cooperative tasks. Aware of the inherent limitations and modeling inaccuracies in such approaches, I also investigate robustness guarantees to ensure reliable performance under uncertainty. Any discussions with me on the topics and applications are warmly welcomed.