讲座题目: Advances in Machine Learning Technologies for Microwave Design Automation
报告人:Qi-jun Zhang（张齐军）教授
Fellow of IEEE
Fellow of Canadian Academy of Engineering
Fellow of Engineering Institute of Canada
Chancellor’s Professor, Carleton University, Ottawa, Canada
时间：2025年2月28日， 10:00-11:00am
地点：九龙湖信息大楼1134会议室
摘要: Electromagnetic-based modeling and optimization are essential for designing RF/microwave components and circuits which are essential building blocks for wireless systems in communication networks, IoT and autonomous systems. This talk explores machine learning technologies for microwave design automation. Methods for inverse modeling, knowledge-based neural networks, neuro-space mapping, and multiphysics based behavioral modeling will be presented. Several types of neural network formulations will be explored for microwave applications such as MLPs, Convolutional neural networks, recurrent neural networks, LSTM, Generative-Adversarial networks, and reinforcement learning. Applications of these machine learning technologies for electromagnetic/multiphysics oriented modeling and optimization and for nonlinear device and circuits behavioral modeling will be described.
报告人简介:
QI-JUN ZHANG received the BEng degree from Nanjing University of Science and Technology, Nanjing, China in 1982, and the Ph.D. degree in electrical engineering from McMaster University, Hamilton, ON, Canada, in 1987. He was a Research Engineer with Optimization Systems Associates Inc., Dundas, ON, Canada, during 1988–1990, developing advanced optimization software for microwave modeling and design. In 1990, he joined the Department of Electronics, Carleton University, Ottawa, ON, Canada, where he is currently a Chancellor’s Professor. He is an Author of the book Neural Networks for RF and Microwave Design (Boston, MA, USA: Artech House, 2000), a co-editor of Modeling and Simulation of High-Speed VLSI Interconnects (Boston, MA, USA: Kluwer, 1994), and a co-editor of Simulation-Driven Design Optimization and Modeling for Microwave Engineering (London, U.K.: Imperial College Press, 2013). His research interests include modeling, optimization, and machine learning for high-speed/high-frequency electronic design. He was twice a Guest-Editor for the Special Issues on Applications of ANN for RF/Microwave Design for the International Journal of RF/Microwave Computer-Aided Engineering (1999, 2002), a Guest Co-Editor for the Special Issue on Machine Learning in Microwave Engineering for the IEEE Microwave Magazine (2021) and a Guest-Editor for the Special Issue on AI and Machine Learning Based Technologies for Microwaves for the IEEE Transactions on Microwave Theory and Techniques (2022).
Dr. Zhang is a Fellow of the IEEE, Fellow of the Canadian Academy of Engineering, and a Fellow of the Engineering Institute of Canada. He is a Distinguished Lecturer of the IEEE EMC Society for 2025-2026. He is a Topic Editor for the IEEE Journal of Microwaves. He is a founding co-chair of the Working Group on AI and Machine Learning Based Technologies for Microwaves in the Future Directions Committee of the IEEE Microwave Theory and Technologies (MTT) Society.
