I am currently a fifth-year PhD student from the department of Electrical and Computer Engineering at the University of Washington,
advised by Prof. Baosen Zhang. My research interests lie broadly in control, machine learning and optimization for cyber-physical energy systems.
Recently, I am developing structured neural network-based controllers with provably guarantees on stability and steady-state efficiency for large-scale systems.
I’m also working on efficient algorithums to overcome the challenges on sample complexity and explorations in learning for real-world applications (e.g., power systems).
I will be on the 2023-2024 academic job market.
Download my CV.
PhD student in Electrical and Computer Engineering, 2019-
University of Washington
MS in Electrical Engineering, 2016-2019
Zhejiang University
BEng in Electrical Engineering and Automation, 2012-2016
Southeast University
[2023/12] I will present our work Leveraging Predictions in Power System Frequency Control: an Adaptive Approach at IEEE CDC 2023 in the session WeA16 Computational Techniques for Automation in Energy Systems. Welcome to drop by our talks.
[2023/12] I will present my research centers around structured control and learning for energy systems in the Meet the Faculty Candidates Poster Session at IEEE CDC 2023. Welcome to drop by our posters.
[2023/09] Our paper on Structured Neural-PI Control with End-to-End Stability and Output Tracking Guarantees is accepted in NeurIPS 2023.
[2023/06] Our paper on Leveraging Predictions in Power System Frequency Control: an Adaptive Approach and Bridging Transient and Steady-State Performance in Voltage Control: A Reinforcement Learning Approach With Safe Gradient Flow are accepted in IEEE CDC 2023.
[2023/05] Honored to be selected as a Rising Star in Cyber-Physical Systems (CPS).
Research experience include:
Research experience include:
Research experience include: