News Release

ECE Faculty Yuanyuan Shi received NSF CAREER Award 2025

Project Title: CAREER: Performance-Guaranteed Learning and Control for Real-world Energy Systems: Stability, Robustness, and Computational Tractability

Website: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2442689&HistoricalAwards=false

Abstract: This five-year project aims to develop performance-guaranteed learning and control for real-world energy systems, with applications to power grid voltage control and building HVAC control. It addresses three central challenges: (1) Incorporating control-theoretic tools into reinforcement learning (RL) to obtain stability and steady-state optimality guarantees. Compared to existing control methods, RL with neural network-based controllers has the potential to significantly reduce transient control costs and achieve faster disturbance recovery for voltage control. (2) Designing operator learning to accelerate control in computationally expensive applications, especially for building control governed by partial differential equations (PDEs). (3) Bridging the gap in deploying learning-based control algorithms to the real world, specifically under time-varying network topologies for power grid voltage control and perturbed sensor inputs in building control. The proposed algorithms will be validated in real- world energy systems, leveraging the NSF-funded DERConnect testbed at UC San Diego.

Bio: Yuanyuan Shi is an Assistant Professor at the Department of Electrical and Computer Engineering at the University of California San Diego. Her research focuses on machine learning, dynamical systems and control, with applications to sustainable energy systems and PDE- governed systems. She received her Ph.D. in Electrical and Computer Engineering (ECE), masters in ECE and Statistics, all from the University of Washington, in 2020. From 2020 to 2021, she was a Postdoctoral Scholar at Caltech. Previously, she received the Schmidt Sciences AI2050 Early Career Fellowship in 2024 and Hellman Fellowship in 2023.