Yujie Tang 唐聿劼

Yujie Tang 

Assistant Professor

Department of Industrial Engineering and Management
College of Engineering
Peking University

Email: yujietang@pku.edu.cn
[ORCID] [Google Scholar]

Postdoc openings on optimization and reinforcement learning are available! See here for more details.

Biography

I am an Assistant Professor in the Department of Industrial Engineering and Management at Peking University.

Before joining Peking University, I was a postdoctoral fellow in the School of Engineering and Applied Sciences at Harvard University, working with Professor Na Li. I received my B.S. degree in Electronic Engineering from Tsinghua University in 2013. I received my Ph.D. degree in Electrical Engineering from the California Institute of Technology in 2019, advised by Professor Steven Low.

I am broadly interested in optimization, control and learning of network systems, and their applications to large-scale cyber-physical networks, by integrating both theoretical tools and engineering insights. Some of my representative research directions include:

  • Distributed zeroth-order optimization: We develop model-free distributed zeroth-order optimization algorithms for multi-agent systems, with rigorous theoretical analysis on their performance.

  • Data-driven learning-based control: We study the design and analysis of data-driven learning-based control methods. Particularly, we are interested in investigating control problems from an optimization viewpoint, by analyzing their optimization landscape properties and designing reinforcement learning algorithms with performance guarantees.

  • Applications in smart grids: We have been working on applying advanced optimization methods to the operation and control of smart grids with distributed energy resources.