Published several papers, including an article in IEEE Transactions on Automatic Control on convergence analysis using quadratic constraints for centralized and distributed mirror descent, a paper in Advances in Neural Information Processing Systems on provably fast convergence of independent natural policy gradient for Markov potential games, and a preprint on arXiv about improving LoRA in privacy-preserving federated learning.
Research Experience
Served as an Assistant Researcher in the Department of Electrical Engineering at Tsinghua University since 2025, focusing on distributed optimization system dynamics, federated learning, and multi-agent reinforcement learning.
Education
Obtained his Ph.D. degree in 2025 from the Department of Mechanical & Industrial Engineering at Northeastern University, advised by Prof. Shahin Shahrampour; was a Ph.D. student in the Department of Industrial Engineering at Texas A&M University (2019-2021); obtained his B.S. degree in Electrical Engineering from the University of Science and Technology of China (2015-2019) as a member of the School of the Gifted Young.
Background
Currently an Assistant Researcher in the Department of Electrical Engineering at Tsinghua University, and a faculty member of the THU-C3I Lab. His research focuses on the theory and novel applications for LLM reasoning, as well as safe and robust AI systems.
Miscellany
Contact: Email is always the best way to reach him.