Doc. Čapek is the principal investigator of the prestigious JUNIOR STAR project, which received a grant from the Grant Agency of the Czech Republic in 2020. The project deals with the development of efficient shape optimization methods, which will allow to find new and atypical shapes for use in wireless, microwave and optical devices. In 2023, together with doc. Kurt Schab of Santa Clara University, USA, the IEEE Antennas and Propagation Society's Professional Paper Award for his paper on modal theory. He is the main architect and leads the development of a toolbox for the MATLAB development environment called AToM (Antenna Toolbox for MATLAB). He is a Senior Member of the IEEE and the Radioengineering Society, an Associate Editor of IET Microwaves, Antennas & Propagation, was a EurAAP delegate and Associate Editor of Radioengineering, as well as a member of the teams of several national and international projects. He has published more than 100 technical and conference papers as author or co-author. The main scientific interests of Assoc. Čapek's main research interests include electromagnetism and small antenna theory, optimization and numerical modelling.
Professor's lecture doc. Miloslav Čapek on the topic: Optimal Inverse Design in Electromagnetism and Its Effective Implementation
27. 9. 2023
Doc. Miloslav Čapek from the Department of Electromagnetic Fields will give a lecture on "Optimal Inverse Design in Electromagnetism and Its Effective Implementation" on Wednesday 11 October at 13:00 in front of the Scientific Council of the Faculty of Electrical Engineering of CTU. His lecture will be streamed live for the public on YouTube.
Optimal design strives to identify the best-performing devices within a given metric, a problem common to all engineering branches. Considering radio frequencies, the challenge might be to find an antenna of a given bandwidth, matching, gain, and electrical size. Unfortunately, optimal design is strictly unfeasible in polynomial time. Many approaches have been adopted over the years to solve such problems in a satisfactory manner, yet our requirements for modern devices push contemporary techniques to their limits eventually rendering them obsolete. In this lecture, the optimal design task will be formulated via the so-called exact reanalysis technique. Altogether, the novel framework deals with non-linear problems by efficiently collecting large data sets for further post-processing based on AI-assisted systems. Its implementation into the commercialized toolbox AToM is demonstrated and accompanied by several showcases involving the inverse design of electrically small antennas, planar lenses, and electromagnetic cloaks. The lecture concludes with a discussion of further advancements in the design of analog wave computers or reconfigurable intelligent surfaces, future technologies that will, undoubtedly, disrupt development in electromagnetics and radio electronics.
