Yuanyuan Shi

Yuanyuan Shi is an Assistant Professor of Electrical and Computer Engineering at the University of California, San Diego. Her research focuses on the intersection of machine learning and control, with applications to sustainable energy systems, smart buildings, and partial differential equation (PDE)-governed systems. She received her Ph.D. from the University of Washington and was a postdoctoral scholar at Caltech, before starting as a faculty member. She is a recipient of the NSF CAREER award and inaugural LANL-UC Anastasio Scholar in 2025, the Schmidt Sciences AI2050 Early Career Fellowship in 2024, and the Hellman Fellowship in 2023.

AI2050 Project

People spend a majority of time in different indoor spaces and buildings, where indoor air quality significantly impacts our health, well-being, and learning. At the same time, buildings account for 40% of global energy consumption and over one-third of total carbon emissions. The goal of this project is to investigate the foundation of neural operator learning for control of large-scale PDE systems with safety and stability guarantees. Yuanyuan Shi will validate the proposed AI-based PDE control framework for indoor climate modeling and control in a real-world office building to balance pathogen exposure, occupant comfort, and carbon emissions.