IEEE Educational Events

The role of Electromagnetic (EM) fields in our lives has been increasing. Communication, remote sensing,integrated command/ control/surveillance systems, intelligent transportation systems, medicine, environment,education, marketing, and defense are only a few areas where EM fields have critical importance. We have witnessedthe transformation from Engineering Electromagnetics to Electromagnetic Engineering for the last few decades afterbeing surrounded by EM waves everywhere. Among many others, EM engineering deals with broad range of problemsfrom antenna design to EM scattering, indoor–outdoor radiowave propagation to wireless communication, radarsystems to integrated surveillance, subsurface imaging to novel materials, EM compatibility to nano-systems,electroacoustic devices to electro-optical systems, etc. The range of the devices we use in our daily life has extendedfrom DC up to Terahertz frequencies. We have had both large-scale (kilometers-wide) and small-scale (nanometers)EM systems. A large portion of these systems are broadband and digital and must operate in close proximity thatresults in severe EM interference problems. Engineers must take EM issues into account from the earliest possible designstages. This necessitates establishing an intelligent balance between strong mathematical background (theory),engineering experience (practice), and modeling and numerical computations (simulation).This Distinguished/keynote lecture aims at a broad-brush look at current complex EM problems as well as certainteaching / training challenges that confront wave-oriented EM engineering in the 21st century, in a complex computerand technology-driven world with rapidly shifting societal and technical priorities.

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.