About me

I am a Postdoc in Industrial and System Engineering at the University of Southern California. I received my Ph.D. in Electrical Engineering in 2023 and my M.Eng. in Electrical Engineering in 2022 at the University of Minnesota. I received my B.E. in Automation from the University of Science and Technology of China in 2018. Please see my CV for more details.

My research interest is in the theoretical aspect of distributed optimization and differential privacy for machine learning. My recent work focuses on (1) understanding federated learning from different perspectives and resolving existing problems in federated learning, including data heterogeneity, communication efficiency, and differential privacy, (2) understanding distributed optimization algorithms and designing system-specific algorithms and making connections to signal processing and control theory, and (3) designing differentially private optimization algorithms with theoretical guarantees. For more details, please see my publications.