EMC Distinguished Lecture Prof. Qi-jun Zhang at Otto von Guericke University Magdeburg
Electromagnetic Compatibility Distinguished Lecturer Talk by Prof. Qi-Jun Zhang (Carleton University, Canada)
Quantum Computing for Machine Learning, Electromagnetic Simulation and Applications to EMC Analysis
Abstract: Quantum computing attracts increasing attention from the computation community in recent years. In certain cases, quantum algorithms has the potential of exponential speedups over their classical counterparts running on classical computers. Quantum computing opens many new opportunities for solving large-scale problems, and simulating complex physical systems. In this talk, we explore quantum computing for AI/machine learning oriented computations, and application of quantum computing in solving electromagnetic problems. Preliminary exploration of quantum computing for solving electromagnetic field simulation problems have been conducted by researchers, using such as Transmission Line Matrix (TLM), Method of Moments (MoM) and Finite-Element Method (FEM) formulations. We present two types of quantum computing approaches for electromagnetic simulation, one is a complete quantum computing approach, utilizing Harrow–Hassidim–Lloyd (HHL) algorithm; another one is a hybrid classical/quantum computing approach utilizing Variational Quantum Algorithm (VQA). New formulations of electromagnetic equations such as FEM equations, into quantum-compatible format will be described. Methods to prepare electromagnetic field excitation vectors into quantum states will be described. Methods to determine various hyperparameters in quantum computing based electromagnetic simulation will be described. Potential applications for EMC analysis will be explored.
Biography: Dr. Qi.jun 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. He also 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.
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- Universitätsplatz 2
- Magdeburg, Sachsen-Anhalt
- Germany 39106
- Building: 09
- Room Number: 11
- Starts 05 May 2026 08:00 PM UTC
- Ends 12 May 2026 10:00 PM UTC
- No Admission Charge