Yi Zhou

Yi Zhou is an Associate Professor in the Department of Computer Science and Engineering at Texas A&M University. His research focuses on machine learning theory, optimization, and their applications in engineering systems such as EDA/CAD, HPC, and multi-agent systems. He holds a Ph.D. in Electrical and Computer Engineering from The Ohio State University (2018) and a B.S. in Electrical Engineering from Beijing Institute of Technology (2013). Prior roles include Assistant Professor at the University of Utah (2019–2024) and a postdoc fellowship at Duke University (2018–2019).

Research interests include nonconvex optimization, reinforcement learning, LLM applications, and statistical learning theory. His work addresses challenges in resource-efficient task scheduling, constrained multi-agent systems, and imbalanced data learning. Notable awards include the NSF CAREER Award (2023) and a NeurIPS Spotlight Paper (2018).

Current projects involve funded Ph.D. positions in LLM applications, optimization theory, and reinforcement learning. Advising emphasizes self-motivated students with strong mathematics, optimization, or RL backgrounds.