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Prof. Q. J. Zhang, Ph.D.
Fellow of IEEE. Chancellor’s Professor, Carleton University, Canada
AI and Machine Learning for Microwaves — Past, Present and Future Trends
Abstract—Machine learning for microwave applications started in the 1990s in the form of artificial neural networks (ANN) for RF/microwave design. Presently, machine learning and artificial intelligence (AI) have become one of the most active topic areas in microwaves, with applications ranging from microwave design automation, to biomedical, security, intelligent wireless systems, and more. This presentation starts with a brief description of historical developments, and highlights some of the state-of-the-art research, and emerging directions in the area.
Q. J. Zhang received 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 AI/machine learning, modeling and optimization 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 of AI and Machine Learning Based Technologies for Microwaves in the IEEE Transactions on Microwave Theory and Techniques (2022).
Dr. Zhang is a Fellow of the IEEE, a Fellow of the Canadian Academy of Engineering, and a Fellow of the Engineering Institute of Canada. He was an Associate Editor for the IEEE Transactions on Microwave Theory and Techniques (2019-2022). He is a Topic Editor for the IEEE Journal of Microwaves. He co-chairs the Working Group on AI and Machine Learning Based Technologies for Microwaves in the Future Directions Committee of the IEEE Microwave Theory and Techniques (MTT) Society.