Changzhan Gu

Changzhan Gu (Senior Member, IEEE) received the B.S. and M.S. degrees from Zhejiang University, Hangzhou, China, in 2006 and 2008, respectively, the M.S. degree from the University of Florida, Gainesville, FL, USA, in 2010, and the Ph.D. degree from Texas Tech University, Lubbock, TX, USA, in 2013. Prior to returning to academia, he worked for several years in industry at Google and Marvell in the Bay Area, California. He is currently an Associate Professor with Shanghai Jiao Tong University, Shanghai, China.

Dr. Gu is a TC Member of IEEE MTT28, the Secretary of the IEEE MTT-S Shanghai Chapter, and selected as the IEEE MTT-S Distinguished Microwave Lecturer (DML) for 2026-2028. He received the IEEE MTT-S Outstanding Young Engineer Award in 2023, the IEEE Sensors Council Early Career Technical Achievement Award in 2019, and the IEEE MTT-S Graduate Fellowship for Medical Applications in 2013. He served as the TPC Chair of the 2022 IEEE International Microwave Biomedical Conference (IMBioC) and has been a TPRC member of the IEEE International Microwave Symposium (IMS) since 2018. Dr. Gu is an Associate Editor for the IEEE Transactions on Microwave Theory and Techniques (T-MTT), the IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology (J-ERM), and the IET Microwave, Antennas & Propagation (MAP). His research interests include short-range microwave sensing technologies and their medical and human tracking applications.

Microwave biomedical radar has achieved significant advancements, enabling transformative healthcare applications specifically for home-based care. Unlike conventional contact-based instruments that can cause discomfort, this non-invasive technology is ideal for continuous monitoring. This presentation will first detail key hardware innovations—including radar miniaturization, and enhanced accuracy and sensitivity—that are critical for deploying portable devices in residential settings. It will then explore specialized RF processing and AI techniques for extracting medical-grade physiological data from radar signals. Finally, the talk will highlight the technology’s breakthrough healthcare applications, from specific clinical applications like post-operative monitoring to broader home-based management. This includes revolutionizing remote patient monitoring, elderly fall detection, and chronic disease tracking for proactive, comprehensive home care.