Speakers

Yize Chen is an assistant professor with ECE Department at the University of Alberta. He got his Ph.D. degree in Electrical and Computer Engineering from University of Washington in 2021; and his undergraduate degree from Chu Kochen College at Zhejiang University in 2016. He was a postdoctoral researcher at the Computing Sciences Area of Lawrence Berkeley National Lab. He has also held multiple research positions at ISO New England, Microsoft Research, Los Alamos National Laboratory, and Harvard Medical School, working on a set of novel projects related to data centers, power grid infrastructures, biological dynamics and the built environment. Previously he was an assistant professor at HKUST. Yize’s research focuses on the intersection between control, optimization and machine learning, and he is interested in designing cyber-physical systems, especially power systems with performance guarantees. He is also committed to achieving sustainable and autonomous clean energy systems. He is also a recipient of several best paper and prize paper awards at IEEE PES General Meeting (2024, 2022), Power Systems Computation Conference (PSCC) (2020), and ACM e-Energy (2019).

Xin Chen is an Assistant Professor in the Department of Electrical and Computer Engineering at Texas A&M University. Dr. Chen directs the Smart Power, Energy and Decision-making (SPEED) Lab at TAMU ECE. His research lies in the intersection of control, optimization, and AI for developing scalable data-driven decision-making theories, algorithms, and tools to advance the intelligence, reliability, and sustainability of modern power and energy systems. Dr. Chen received the Ph.D. degree in electrical engineering from Harvard University, the master’s degree in electrical engineering and two bachelor’s degrees in engineering and economics from Tsinghua University. Dr. Chen was a Postdoctoral Associate affiliated with MIT Energy Initiative at Massachusetts Institute of Technology. Dr. Chen is a recipient of the IEEE PES Outstanding Doctoral Dissertation Award, IEEE Transactions on Smart Grid Top-5 Papers, the Best Research Award at the 2023 IEEE PES Grid Edge Conference, and several best paper awards in top IEEE control and power conferences.

Yuanyuan Shi is an Assistant Professor in the Department of Electrical and Computer Engineering (ECE) at UC San Diego. She received her Ph.D. in ECE, masters in ECE and Statistics from University of Washington, Seattle in 2020. She was a postdoc fellow at Caltech from 2020-2021. Yuanyuan’s research lies in machine learning, dynamical systems and control, with applications to sustainable energy systems. She is a recipient of the NSF CAREER Award in 2025, Schmidt AI2050 Early Career Fellowship in 2024, Hellman Fellowship in 2023, and best paper nominations from L4DC 2025 and ACM e-Energy 2022. [Website]