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Prof. Qi-Jun Zhang
Chancellor’s Professor, Department of Electronics, Carleton University, Ottawa, Canada
Dr. Zhang received the B.Eng. degree in EE from Nanjing University of Science and Technology (Nanjing) in 1982, and the Ph,D. degree in EE from McMaster University (Hamilton, Ontario) in 1987. He was a researcher engineer in Optimization Systems Associates Inc. (Dundas, Ontario) during 1988-1990 developing advanced microwave optimization software. He joined the Department of Electronics, Carleton University in 1990, where he is currently a Chancellor’s Professor.
Dr. Zhang’s research area is AI/machine learning, and optimization for designing high-speed/high-frequency components/packages and systems, which are building blocks of computers, wireless and wired systems in telecommunications, internet, and intelligent and autonomous systems.
Dr. Zhang advanced the theory and practice of microwave active and passive computer-aided design with innovations in linear and nonlinear device modeling and circuit optimization for which he received the IEEE Fellowship in 2006.
Dr. Zhang is one of the pioneers of neural networks and machine learning for microwaves which started in the early 1990s. Dr. Zhang’s continuous innovations in this area for over 30 years have established many research milestones, and contributed to the substantial development of the area. He authored (with Prof. K.C. Gupta) the first book of the area (Neural Networks for RF and Microwave Design, Boston, Artech House, 2000), and developed the first software (NeuroModeler, 1998) of the area. His neural network based modeling technology was adopted in industrial projects such as the Advanced Embedded Passives Technology Consortium (2000-2003) funded by the US Department of Commerce and the National Center for Manufacturing Sciences (Michigan, USA). In 2012, neural network based transistor modeling technology pioneered by him and his student became a primary feature of Agilent/Keysight IC-CAP software, the microwave industry’s dominant modeling tool. Over 360 technical papers archive his pioneering contributions. Example of publication: Q.J. Zhang, K.C. Gupta and V.K. Devabhaktuni, “Artificial neural networks for RF and microwave design: from theory to practice,” IEEE Trans. Microwave Theory Techniques, vol. 51, 2003, pp. 1339-1350.
Dr. Zhang’s paper with his former PhD students F. Feng, W.C. Na, J. Jin, J.N. Zhang, W. Zhang, titled “Artificial neural networks for microwave computer-aided design: the state of the art,” IEEE Transactions on Microwave Theory and Techniques, vol. 70, no. 11, pp. 4597-4619, Nov. 2022 became hugely influential. The paper is ranked the #1 most frequently accessed paper in a given month among all papers of IEEE Transactions on Microwave Theory and Techniques, for each and every month for 11 months in a row since its publication in November 2022. At the time of writing this paragraph, the latest monthly statistics (October 2024) shows that this paper is currently still the #1 most frequently accessed paper of the IEEE Transactions on Microwave Theory and Techniques.
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