Computational Electromagnetics: From Basics to Mastery
Computational Electromagnetics (CEM) is an interdisciplinary field that combines principles from electrical engineering, physics, mathematics, and computer science to simulate and analyze electromagnetic phenomena. It serves as a cornerstone for the design and optimization of practical systems such as antennas, microwave circuits, radars, satellites, wireless communication devices, and emerging applications in nanophotonics and biomedical imaging. The increasing complexity of modern systems— featuring irregular geometries, inhomogeneous media, and multiscale behaviors—necessitates robust and efficient modeling and simulation techniques.
Over the past decades, CEM has evolved to address challenges associated with electrically large structures, multiphysics environments, and high-frequency regimes. Recent advancements in computing technologies—especially GPUs and domain-specific hardware—have enabled researchers to solve problems with billions of unknowns, while hybrid numerical schemes and parallel implementations ensure scalability and efficiency. Recent trends also include the use of machine learning-based surrogate models, which are trained to approximate the behavior of computationally expensive simulations, enabling faster predictions without compromising accuracy.
This lecture will begin by covering the theoretical foundations and numerical implementations of classical CEM methods, including the Method of Moments (MoM), Finite Element Method (FEM), Finite Difference (FD), and Finite Difference Time Domain (FDTD) method. Emphasis will be placed on their mathematical formulation, discretization strategies, and computational aspects. In the second part, the focus will shift to advanced techniques used to tackle contemporary challenges in CEM, such as hybrid methods, domain decomposition, and large-scale parallel solvers. Current trends that are reshaping the future of the field— such as the integration of data-driven machine learning approaches into electromagnetic modeling workflows—will be briefly highlighted. Real-world case studies will be presented to illustrate the practical applications of these methods in the simulation of electromagnetic radiation and scattering problems.
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- 200 University Ave W
- Waterloo, Ontario
- Canada N2L 3G1
- Building: E7
- Room Number: PSE 7363 Faculty Hall
- Starts 28 June 2026 04:00 AM UTC
- Ends 09 July 2026 04:00 AM UTC
- No Admission Charge
Speakers
Professor Özgün
Computational Electromagnetics: From Basics to Mastery
Computational Electromagnetics (CEM) is an interdisciplinary field that combines principles from electrical engineering, physics, mathematics, and computer science to simulate and analyze electromagnetic phenomena. It serves as a cornerstone for the design and optimization of practical systems such as antennas, microwave circuits, radars, satellites, wireless communication devices, and emerging applications in nanophotonics and biomedical imaging. The increasing complexity of modern systems— featuring irregular geometries, inhomogeneous media, and multiscale behaviors—necessitates robust and efficient modeling and simulation techniques.
Over the past decades, CEM has evolved to address challenges associated with electrically large structures, multiphysics environments, and high-frequency regimes. Recent advancements in computing technologies—especially GPUs and domain-specific hardware—have enabled researchers to solve problems with billions of unknowns, while hybrid numerical schemes and parallel implementations ensure scalability and efficiency. Recent trends also include the use of machine learning-based surrogate models, which are trained to approximate the behavior of computationally expensive simulations, enabling faster predictions without compromising accuracy.
This lecture will begin by covering the theoretical foundations and numerical implementations of classical CEM methods, including the Method of Moments (MoM), Finite Element Method (FEM), Finite Difference (FD), and Finite Difference Time Domain (FDTD) method. Emphasis will be placed on their mathematical formulation, discretization strategies, and computational aspects. In the second part, the focus will shift to advanced techniques used to tackle contemporary challenges in CEM, such as hybrid methods, domain decomposition, and large-scale parallel solvers. Current trends that are reshaping the future of the field— such as the integration of data-driven machine learning approaches into electromagnetic modeling workflows—will be briefly highlighted. Real-world case studies will be presented to illustrate the practical applications of these methods in the simulation of electromagnetic radiation and scattering problems.
Biography:
Özlem .zgün is currently a full professor in the Department of Electrical and Electronics Engineering and vice dean of the Faculty of Engineering at Hacettepe University, Ankara, Turkey. She received her B.Sc. and M.Sc. degrees from Bilkent University and her Ph.D. from Middle East Technical University (METU), all in Electrical and Electronics Engineering. She was a postdoctoral researcher at Penn
State University, US.
Her research interests include various topics in computational electromagnetics and radiowave propagation, including electromagnetic radiation and scattering, numerical methods, domain decomposition methods, transformation electromagnetics, stochastic electromagnetic problems and optimization techniques. She has authored over 130 refereed publications in international journals, book (MATLAB-based Finite Element Programming in Electromagnetic Modeling, CRC Press, 2018), book chapters and conference proceedings.
Dr. .zgün is a senior member of IEEE and URSI and a past chair of the URSI Turkey steering committee. Her awards include the METU Best Ph.D. Thesis Award (2007), the Felsen Fund Excellence in Electromagnetics Award (2009), and Hacettepe University Science Award (2024). She was recognized among the world's top 2% most influential scientists (Stanford University & Elsevier, 2023–2025).