Next-generation AI for semiconductor and power electronics technologies
About Me
Xinze Li (Member, IEEE) received the bachelor’s degree in Electrical Engineering from Shandong University, Shandong, China, in 2018, and the Ph.D. degree in Electrical and Electronic Engineering from Nanyang Technological University, Singapore, in 2023. He joined the University of Arkansas, USA, as a postdoctoral research fellow in 2024 and a lecturer in 2025. He is currently an Assistant Professor with the Department of Electrical and Computer Engineering, Florida State University, Tallahassee, FL, USA.
His research interests center on next-generation AI for power electronics technologies, including AI for power electronics simulation and modeling, maintenance and reliability, and process automation, as well as digital twins and process optimization for semiconductor fabrication. His work is driven by three core AI themes: physical AI, explainable AI, and agentic AI.
News and Updates
September 2026[Publication]Our invited paper “Fundamentals of Artificial Intelligence for Power Electronics” is published (early access) in IEEE Transactions on Industrial Electronics. IEEE Xplore · ResearchGate
September 2026[Publication]“Reforming Power Electronics Education in the Era of AI: A Pilot Course by the University of Arkansas Power Group [Expert View]” is published in IEEE Power Electronics Magazine. IEEE Xplore
August 2026[Appointment]I joined Florida State University as an Assistant Professor in Electrical and Computer Engineering.
July 2026[Publication]“Quantum Computing for Smart Grid” is the cover story of the July 2026 issue of Nature Reviews Electrical Engineering. Paper
May 2026[Publication]Our roadmap review “Quantum Computing for Smart Grid” was published in Nature Reviews Electrical Engineering. Paper
March 2026[Award]Our physics-informed autonomous-agent research received the IAAI Deployed Application Award at AAAI 2026. Paper
October 2025[Tutorial]We presented the IEEE ECCE tutorial “Reimagine Power Electronics Design with Artificial Intelligence.” Slides
March 2025[Tutorial]We delivered the IEEE APEC Professional Education Seminar “AI in Power Electronics Design: Present and Future.” Slides
October 2024[Publication]“PE-GPT: A New Paradigm for Power Electronics Design” introduced a domain-specific generative-AI framework for power-electronics design. Paper
March 2024[Publication]Our PANN paper established physics-in-architecture recurrent modeling for power converters. Paper
July 2023[Award]I was the sole recipient of the NTU Graduate College Collaborative Research Award for the 2023–2024 academic year.
March 2023[Award]Our work on data-driven ZVS modeling received an APEC Outstanding Presentation Award. Paper
September 2022[Award]“Automatic Triple Phase-Shift Modulation for DAB Converter With Minimized Power Loss” received an IEEE IAS Prize Paper Award, Second Prize. Paper
Upcoming Sessions
IEEE APEC 2027 · Professional Education Seminar
S02 - Learning AI for Power Electronics from an Algorithmic Perspective: A Practitioner’s Guide
The hands-on session will use an AI coding agent and Google Colab to build a neural-network model of magnetic core loss. Experiments cover data exploration, comparison with the generalized Steinmetz equation, feature scaling, and validation. Hands-on preparation guide and lab preview
IEEE APEC 2027 · Industry Session
IS08 - Advancing Power Electronics with Artificial Intelligence: From Research Frontiers to Industry Applications
Openings
PhD students · Spring 2027–Spring 2028
I am recruiting motivated PhD students to join my research group at Florida State University in AI for power electronics and semiconductor manufacturing.