At present, computational electromagnetics (CEMs) methods play an important role in rapid modeling and design of electromagnetic (EM) systems and their industrial applications. Virtual prototyping based on computational electromagnetics is currently widely adopted in electrical and electronic systems design because of the high accuracy guaranteed by many numerical methods for the solution of Maxwell’s equations in a wide range of frequency from DC to hundreds of GHz or even in the THz range. With the continuous increase of integration and complexity in integrated circuits, electromagnetic compatibility (EMC) and signal integrity (SI) issues have consequently become very important. Hence, numerical modeling and simulation play a key role in the design of electromagnetic systems, and new algorithms and computational capabilities are increasingly essential to tackle EMC and SI issues. In this perspective, fast algorithms to allow an accurate and efficient analysis of complex EM problems are strongly requested. Additionally, semi-analytical methods can offer elegant and accurate solutions to complex EM problems.

Furthermore, active devices are often affected by heat conduction, potentially leading to electrothermal breakdown. Under such circumstances, predictive simulations must rely on multiphysics computational approaches as opposed to electromagnetics‐only methods. Parallel computing can offer new potential to consolidated methods.

Real-life applications are typically complex and their electromagnetic models electrically large. This calls for accurate wideband model order reduction/macromodeling techniques that make their simulation feasible. Furthermore, in the optimization of large platforms (aircrafts, automotive), design parameters are very likely affected by uncertainty that needs to be taken into account through accurate and efficient uncertainty quantification techniques.