Princeton Faculty Spotlight Series Featured Faculty: Professor Minjie Chen Date: November 5, 2024 Time: 12:00 pm Speaker: Minjie Chen, Princeton University Registration: Participate remotely by visiting [ https://princeton.zoom.us/meeting/register/tJIsfuCqqTotGdKxqOkFvfDbjh6uEDNpH... | this link ] WEBINAR Followed by Live Q&A/Discussion. Register [ https://princeton.zoom.us/meeting/register/tJIsfuCqqTotGdKxqOkFvfDbjh6uEDNpH... | here ] . Minjie Chen is an Associate Professor of Electrical and Computer Engineering and the Andlinger Center for Energy and the Environment at Princeton University. He received his Ph.D. in Electrical Engineering and Computer Science from MIT in 2015 and his B.S. in Electrical Engineering from Tsinghua University in 2009, both with honors. He His research interests include high-frequency power electronics, power architecture, power magnetics, data-driven methods, and the design of high-performance power electronics for critical applications. Prof. Chen is a recipient of the IEEE PELS Richard M. Bass Outstanding Young Power Electronics Engineer Award, the Princeton SEAS Junior Faculty Award, the NSF CAREER Award, five IEEE Transactions on Power Electronics Prize Paper Awards, and the MIT EECS D. N. Chorafas Ph.D. Thesis Award. He was listed on the Princeton Engineering Commendation List for Outstanding Teaching multiple times. Dr. Chen is an IEEE senior member and the Vice Chair of IEEE PELS TC10 Design Methodologies. Professor Chen will present his research, followed by a Q&A/discussion period. The NextG Faculty Spotlight Series is hosted by Princeton NextG, an initiative of Princeton’s School of Engineering and Applied Sciences. The NextG Initiative at Princeton is creating the foundation for intelligent networks of the future across wireless, backbone networking, and cloud systems. The initiative focuses on cross-disciplinary approaches, bringing theory to practice, and covering the ‘full stack’ from the underlying technological fabric in integrated electronic and photonic circuits and systems, edge networks, IOT and cloud, to foundational theory, algorithms and AI approaches that make these networks scalable, efficient, secure, and accessible.