报告题目：Physics-Assisted Machine Learning for Wave Sensing and Imaging

报告嘉宾：陈旭东，新加坡国立大学 教授

报告时间：2025年9月22日 9:30

报告地点：w88win优德中心校区无机-超分子楼二楼报告厅

主持人：洪德成

报告摘要

　　Machine learning (ML) has attracted significant attention for addressing challenges in wave imaging and sensing. However, many approaches treat ML as a black box, overlooking decades of insights rooted in wave physics and rigorous mathematical analysis. This talk underscores the importance of thoroughly understanding the forward problem that underpins these inverse tasks, and demonstrates how integrating mathematical, physical, and engineering intuition can lead to more efficient and elegant solutions. Three imaging and sensing tasks will be presented. First, we examine millimeter-wave multiple-input multiple-output imaging, showcasing how physics-assisted ML can improve reconstruction quality. Second, we present a highly accurate and efficient ML classifier for 77 GHz FMCW radar, where low-dimensional physics-derived features enable reliable classification of road targets. Third, we address the integration of sensing and communication (ISAC) by combining ML with inverse scattering problem modeling. Furthermore, any question regarding IEEE Transactions on Geoscience and Remote Sensing paper submission and review will be answered.

嘉宾简介

　　Prof. Chen received the B.S. and M.S. degrees from Zhejiang University and the Ph.D. degree from the Massachusetts Institute of Technology. Since 2005, he has been with the National University of Singapore, Singapore, where he is currently a Professor. His research interests include mainly electromagnetic wave theories and applications, with a focus on inverse problems and computational imaging. He has published 180 journal papers and has authored the book Computational Methods for Electromagnetic Inverse Scattering (Wiley-IEEE, 2018), which has been adopted as a textbook by many undergraduate- and graduate-level courses worldwide. Prof. Chen is a Fellow of IEEE and Fellow of the Electromagnetics Academy. He is currently a Deputy Editor-in-Chief of IEEE Transactions on Geoscience and Remote Sensing (IEEE T-GRS), and he was an Associate Editor of IEEE T-MTT, IEEE T-GRS, and IEEE JERM.

主办单位：

w88win优德

物质模拟方法与软件教育部重点实验室