Artificial intelligence (AI) requires machines to have wisdoms which can be represented by their autonomy, just like what a normal adult in our human being possesses. Making machines have such wisdoms not only requires that the software be dynamically changed according to the changes of environments or situations, but also requires that the hardware be softwarelized, i.e., it can be changeable, reconfigurable, and programmable, in either geometries and/or materials. That is to say, all electronic devices and systems, which constitute the major parts of modern machines, will be changeable in the geometries and/or materials in the AI era, and this can be more and more realizable thanks to the rapid development of flexible electronic materials in recent years.

Electromagnetic (EM) analysis is a foundation for optimally designing modern electronic devices and systems. When the geometries and materials of the devices and systems are dynamically changeable, how can we make an accurate and efficient EM analysis for them? The dynamical modeling and simulation is then inevitable! EM problems are governed by the well-known Maxwell’s equations which can be changed into different forms. The original Maxwell’s equations take a partial differential equation form, but they can be changed into an integral equation form by introducing the Green’s function. Considering the changeable domains of analyzed targets or objects in the AI era, the integral equations will be more suitable for governing the problems because they only discretize the domains of targets. The primary solver for EM integral equations is the method of moments (MoM), but it strongly relies on the high-quality meshes of discretizing solution domains, and this is obviously a serious constraint. Aiming to the difficulty, we develop a robust meshless method in recent years, which can fully overcome or alleviate the problems in the traditional MoM and it could be very useful for the dynamical modeling and simulation for EM interactions with deformable objects. We will introduce the method in details and demonstrate its effectiveness and robustness for solving such EM problems by using numerical examples.

Mei Song Tong received the B.S. and M.S. Degrees from Huazhong University of Science and Technology, Wuhan, China, respectively, and Ph.D. degree from Arizona State University, Tempe, Arizona, USA, all in electrical engineering. Currently, he is the Distinguished/Permanent Professor, Head of Department of Electronic Science and Technology, and Vice Dean of College of Microelectronics, Tongji University, Shanghai, China. He has also held an adjunct professorship at the University of Illinois at Urbana-Champaign, Urbana, Illinois, USA, and an honorary professorship at the University of Hong Kong, China. He has published more than 500 papers in refereed journals and

conference proceedings and co-authored six books or book chapters. His research interests include electromagnetic field theory, antenna theory and technique, modeling and simulation of RF/microwave circuits and devices, interconnect and packaging analysis, inverse electromagnetic scattering for imaging, and computational electromagnetics.

Prof. Tong is a Fellow of the Electromagnetics Academy, Fellow of the Japan Society for the Promotion of Science (JSPS), and Full Member (Commission B) of the USNC/URSI. He has been the chair of Shanghai Chapter since 2014 and the chair of SIGHT committee in 2018, respectively, in IEEE Antennas and Propagation Society. He has served as an associate editor or guest editor for some well-known international journals, including IEEE Antennas and Propagation Magazine, IEEE Transactions on Antennas and Propagation, IEEE Transactions on Components, Packaging and Manufacturing Technology, International Journal of Numerical Modeling: Electronic Networks, Devices and Fields, Progress in Electromagnetics Research, and Journal of Electromagnetic Waves and Applications, etc. He also frequently served as a session organizer/chair, technical program committee member/chair, and general chair for some prestigious international conferences. He was the recipient of a Visiting Professorship Award from Kyoto University, Japan, in 2012, and from University of Hong Kong, China, 2013. He advised and coauthored 12 papers that received the Best Student Paper Award from different international conferences. He was the recipient of the Travel Fellowship Award of USNC/URSI for the 31th General Assembly and Scientific Symposium (GASS) in 2014, Advance Award of Science and Technology of Shanghai Municipal Government in 2015, Fellowship Award of JSPS in 2016, Innovation Award of Universities’ Achievements of Ministry of Education of China in 2017, Innovation Achievement Award of Industry-Academia-Research Collaboration of China in 2019, Chapters Award of IEEE New Jersey Section, USA, in 2019, “Jinqiao” Award of Technology Market Association of China in 2020, and Baosteel Education Award of China in 2021. In 2018, he was selected as the Distinguished Lecturer (DL) of IEEE Antennas and Propagation Society for 2019-2022.