应认知无线电与信息处理省部共建教育部重点实验室、广西无线宽带通信与信号处理重点实验室、广西精密导航技术与应用重点实验室邀请，南方科技大学刘凡助理教授、复旦大学王健青年研究员将于2022年12月2日通过腾讯会议网络平台开展线上讲学，欢迎全校师生踊跃参加。报告具体安排如下：
时间：2022年12月2日（周五）上午9：00-11：00
地点：腾讯会议（会议号：147-448-692）
报告一题目：On the Fundamental Tradeoff of Integrated Sensing and Communications Under Gaussian Channels
主讲人：Fan Liu
摘要：Integrated Sensing and Communication (ISAC) is recognized as a promising technology for both the next-generation wireless networks and radar systems. In this talk, we consider a P2P ISAC model under vector Gaussian channels, and propose to use the CRB-rate region as a basic tool for depicting the fundamental sensing and communications (S&C) tradeoff. We characterize the S&C performance at the two corner points of the CRB-rate region. In particular, we derive the high-SNR communication capacity at the sensing-optimal point, and provide lower and upper bounds for the sensing CRB at the communication-optimal point.
主讲人简介：Fan Liu is currently an Assistant Professor of the Department of Electronic and Electrical Engineering, Southern University of Science and Technology (SUSTech), China. His research interests include the general area of signal processing and wireless communications, and in particular in the area of Integrated Sensing and Communications (ISAC). He is the Founding Academic Chair of the IEEE ComSoc ISAC Emerging Technology Initiative (ISAC-ETI), an Associate Editor for the IEEE Communications Letters and the IEEE Open Journal of Signal Processing, and a Guest Editor of the IEEE Journal on Selected Areas in Communications and the IEEE Wireless Communications. He was also an organizer and Co-Chair for numerous workshops and special sessions in flagship IEEE/ACM conferences, including ICC, GLOBECOM, MobiCom, ICASSP, and SPAWC. He is the TPC Co-Chair of the 2nd and 3rd IEEE Joint Communication and Sensing Symposium (IEEE JC&S). He was listed in the World's Top 2% Scientists by Stanford University for citation impact in 2021 and 2022. He was the recipient of the IEEE Signal Processing Society Young Author Best Paper Award of 2021, and the Best Ph.D. Thesis Award of Chinese Institute of Electronics of 2019.
报告二题目：信息处理中的稀疏优化
主讲人：王健
摘要：稀疏优化在大数据时代中已发挥了显著的计算优势与应用价值，近年来引发了电气工程、计算机、应用数学等领域的广泛兴趣。本报告将介绍稀疏优化在信息处理领域中的一些新的研究进展，包括基于压缩感知的新冠肺炎检测、子空间相位恢复等。
主讲人简介：王健，博士，复旦大学青年研究员、博士生导师，2013年获高丽大学电子电气计算机博士学位。曾在罗格斯大学、杜克大学、首尔国立大学从事教学科研工作。近年来在IEEE TIT、TSP、TKDE、JSTSP等信息领域权威期刊及会议上发表论文50余篇，多篇入选IEEE TSP热点论文、ESI高被引论文等，SCI引用800余次。曾获IEEE信号处理协会青年最佳论文奖提名、装发天智杯人工智能挑战赛优秀奖等。担任Frontier信号处理、DCN等杂志编委。研究方向包括统计与机器学习、图卷积神经网络、稀疏与低秩优化等。