报告题目：Can You Identify an Electromagnetic Photo? – EMC Analysis Enhanced by Artificial Intelligence

IEEE EMC-S Distinguished Lecturer

时间：2026年3月5日（周四）14：00-15：30

地点：无线谷A3楼3412会议室

组织：IEEE Nanjing Section AP-S/MTT-S/EMC-S Joint Chapter

    毫米波全国重点实验室

摘要：In recent years, the artificial intelligence (AI) technology provides a powerful tool for solving electromagnetic problems, and there has been many successful stories for their applications on microwave device and antenna designs. The radiated near-field can be taken as an electromagnetic photo of an unknown EMI radiation source. This photo contains a lot of intrinsic information about the radiation source, such as its 3-meter radiation, coupling characteristics with nearby sensitive devices, as well as information about the position and polarization of the radiation source itself. But due to the inability of the human eye to see electromagnetic waves, our ability to identify electromagnetic photos is much lower than that of ordinary photos. AI has achieved significant results in facial recognition. This allows us to use AI to process electromagnetic photos and extract the useful information for EMI analysis from the features of the photos, such as 3-meter far-field and far-field radiation pattern.

This talk will start with a brief overview of AI and its applications in the EMC area. Then several different ways to enhance the near-field scanning by AI are presented. The Green’s function hybrid with artificial neural network (ANN) is developed for EMI estimation. The Green’s function of a dipole array with fixed source points is taken as input and the radiated field at any given observation point is taken as the output of ANN. We use the powerful mapping ability of ANN to replace the matrix-vector multiplication between Green’s function and dipole moments in the traditional dipole model, so that the ANN can be used to predict the near-field from unknown EMI source. Next, a deep convolutional neural network (DCNN) hybrid with the plane wave spectrum is proposed. By leveraging plane wave expansion, the spatial magnetic near-field data are converted into the spectrum domain, serving as the input for the DCNN model. DCNN’s output is the 3-meter electric far field. It enables the output of DCNN (3-meter far-field) insensitive to variations in the near-field scanning height. Finally, the physics-informed neural network (PINN) is introduced for near-field prediction, where the wave equation is integrated with the deep neural network. Therefore, the PINN is capable of efficiently interpolating and extrapolating the scanned near-field fields.

报告人简介：

Xing-Chang Wei received the Bachelor, Master, and PhD degrees in the electromagnetic field and microwave engineering from Xidian University, China, in 1995, 1998, and 2001 respectively. From 2001 to 2010, he was with the A*STAR Institute of High Performance Computing, Singapore, as a Research Fellow, Senior Research Engineer, and then Research Scientist. He was the visiting scholar of University of Illinois Urbana-Champaign in 2015. In 2010, he joined Zhejiang University, China, as a Full Professor.

His main research interests include near-field scanning, power integrity (PI), and electromagnetic interference (EMI) simulation and testing. He has more than 20 years research experiences of the electromagnetic compatibility (EMC) modeling and design of the high-speed printed circuit boards and packaging. He has authored one book, a book chapter, and about 200 papers published in IEEE Transactions and IEEE international conferences. He received the 2007 Singapore Institution of Engineers Prestigious Engineering Achievement Award for his contribution on the development of the reverberation chamber, and New Century Professional Award from China Ministry of Education in 2010.
 He was an IEEE senior member since 2009, and Associate Editor of IEEE Transactions on Electromagnetic Compatibility. He contributed to EMCS/IEEE in several related international conferences, and received the 2019, 2021, 2022 and 2023 Distinguished Reviewer of the IEEE Transactions on Electromagnetic Compatibility. He was the Co-Chair of the Technical Program Committee of 2010 IEEE Electrical Design of Advanced Packaging and Systems Symposium (EDAPS), Technique Paper Co-Chair of 2018 and 2020 IEEE International Symposium on Electromagnetic Compatibility & Asia-Pacific Symposium on Electromagnetic Compatibility (APEMC), and Program Chair of 2012 APEMC. He severed as the TPC members of APEMC and IEEE Workshop on Signal and Power Integrity (SPI) since 2010 and 2015 respectively. He also organized more than 10 workshops/special sessions with EMC topics on APEMC, International Workshop on the Electromagnetic Compatibility of Integrated Circuits (EMC Compo), IEEE International Conference on Computational Electromagnetics (ICCEM), and other conferences since 2011.

His supervised students obtained Best Student Paper Award in 2019 EMC Compo and 2022 APEMC, Young Investigator Training Program in 2017 SPI, Second Student Paper Award in 2016 IEEE MTT-S International Wireless Symposium, Outstanding Paper Award in 15th International Conference on Electronics Packaging Technology (ICEPT), Best Symposium Paper in 2012 APEMC, and Engineering Degree Award issued by China National Graduated Education Steering Committee for Professional Engineering Degree.

中文介绍：

魏兴昌教授分别于1995年、1998年和2001年在中国西安电子科技大学获得电磁场与微波技术专业的学士、硕士和博士学位。2001年至2010年，他任职于新加坡A*STAR高性能计算研究所，先后担任研究员、高级研究工程师及研究科学家。2015年，他成为美国伊利诺伊大学厄巴纳-香槟分校的访问学者。2010年，他加入中国浙江大学，担任全职教授。

他的主要研究兴趣包括近场扫描、电源完整性（PI）以及电磁干扰（EMI）的仿真与测试。他在高速印刷电路板及封装领域的电磁兼容（EMC）建模与设计方面拥有超过20年的研究经验。他著有1部专著、1个书章节，并在《IEEE Transactions》期刊及IEEE国际会议上发表论文约200篇。因在混响室开发方面的贡献，他荣获2007年新加坡工程师学会杰出工程成就奖，并于2010年获得中国教育部新世纪优秀人才奖。

自2009年起，他成为IEEE高级会员，并担任《IEEE Transactions on Electromagnetic Compatibility》期刊副编辑。他在多个相关国际会议中为EMCS/IEEE做出贡献，并荣获2019年、2021年、2022年和2023年《IEEE Transactions on Electromagnetic Compatibility》杰出审稿人奖。他是2010年IEEE先进封装与系统电气设计研讨会（EDAPS）技术程序委员会联合主席，2018年和2020年IEEE国际电磁兼容研讨会暨亚太电磁兼容研讨会（APEMC）技术论文联合主席，以及2012年APEMC的程序主席。自2010年和2015年起，他分别担任APEMC和IEEE信号与电源完整性（SPI）研讨会的技术程序委员会成员。自2011年以来，他还在APEMC、集成电路电磁兼容国际研讨会（EMC Compo）、IEEE国际计算电磁学会议（ICCEM）等会议上组织了10余场以电磁兼容为主题的研讨会/专题会议。

他指导的学生分别荣获2019年EMC Compo最佳学生论文奖、2022年APEMC最佳学生论文奖、2017年SPI青年研究者培训计划奖、2016年IEEE MTT-S国际无线研讨会学生论文二等奖、第15届国际电子封装技术会议（ICEPT）优秀论文奖、2012年APEMC最佳研讨会论文奖，以及中国国家专业学位 指导委员会颁发的工程学位奖。