Physiological Sensing via Signal Processing and Deep Learning

In this talk, we will explore the recent advances in physiological sensing with an emphasis on contact-free sensing via such modalities as camera and radio frequency. We will sample a few representative signal processing and deep learning-based approaches and dive into the design philosophies, aiming at inspiring cross-disciplinary research collaboration. A future perspective on how an emerging collaborative learning paradigm, namely, federated learning, may be used to facilitate crowdsource-based sensing of physiological data will be discussed.

Chai-Wai Wong

NC State University on October 4, 2022 at 1:00 PM in 454 Monteith Research Center
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Wong obtained his bachelor’s degree and a master of philosophy degree from The Hong Kong Polytechnic University, and Ph.D. from the University of Maryland, College Park. His Ph.D. focused on micro signal extraction and analytics under the mentorship of Min Wu. Wong joined NC State after briefly working at a wireless analytics startup as a data scientist. His work has been published in multimedia forensics, signal processing, and social sciences journals. He has taught graduate level courses and mentored graduate and undergraduate students.

ASSIST Distinguished Seminar Series

ASSIST is developing leading-edge systems for high-value applications such as healthcare and IoT by integrating fundamental advances in energy harvesting, low-power electronics, and sensors with a focus on usability and actionable data.