About the Book
This book explores artificial neural networks (ANNs) and their applications in high-frequency engineering, with particular attention to areas such as antenna design, microwave engineering, and microwave photonics. Emphasis is placed on recent advancements in leveraging ANNs for enhanced forward and inverse modeling, local and global optimization, multi-objective design, uncertainty quantification, and design automation, including system synthesis and unsupervised design approaches. The authors discuss a wide range of ANN architectures, including MLPs, RNNs, LSTMs, ResNets, CNNs, graph neural networks, physics-informed neural networks, neuro space mapping techniques, and multi-fidelity models. The book features detailed case studies and benchmarking of ANN techniques against state-of-the-art methods, offering both practical insight and theoretical grounding.
About the Author :
Slawomir Koziel received the M.Sc. and Ph.D. degrees in electronic engineering from Gdansk University of Technology, Poland, in 1995 and 2000, respectively. He also received the M.Sc. degrees in theoretical physics and in mathematics, in 2000 and 2002, respectively, as well as the PhD in mathematics in 2003, from the University of Gdansk, Poland. He is currently a Professor with the Department of Engineering, Reykjavik University, Iceland. His research interests include CAD and modeling of antennas and microwave circuits, simulation-driven design, surrogate-based optimization, machine learning, and artificial intelligence. He has published over 30 book chapters and over 1,300 peer-reviewed research papers. He is a founder and director of Engineering Optimization & Modeling Center at Reykjavik University. Slawomir Koziel is a recipient of Fulbright Scholarship for the academic year 2003/2004. He has served on the Editorial Board of various international journals, program committee member as well as co-organizer of numerous special sessions and workshops at international conferences. He is a Chief Editor of Int. J. Antennas Propag., an Associate Editor of several journals (IET Microwaves Ant. Prop., El. Lett., Int. J. Math. Modeling Num. Opt., Int. J. Numerical Modeling). Dr. Koziel is an IEEE Fellow. He also placed 54 (out of over 200,000) on the 2024 list of top 2% scientists by Stanford University in the field of Networking & Telecommunications. His h-index is 71 with >24,600 citations. Anna Pietrenko-Dabrowska received the M.Sc. and Ph.D. degrees in electronic engineering from Gdansk University of Technology, Poland, in 1998 and 2007, respectively. Currently, she is a Full Professor with Gdansk University of Technology, Poland. She has served as the Associate Editor of Int. J. Num. Modeling, Int. J. Ant. Propag., and Electronics. She has been a guest co-editor of several special issues ISI-ranked journals including Int. J. Num. Modeling, Electronics, and Applied Sciences. She has been a program committee member of international conferences (IEEE MTT-s Int. Conf. Num. EM and Multiphysics Modeling and Optim., Int. Conf. Comp. Science, IEEE Int. Symp. Ant. Propag.). She is a co-author of the monographs Response feature technology for high-frequency electronics. Optimization, modeling, and design automation (Springer, 2024), and Performance-driven surrogate modeling of high-frequency structures (Springer, 2020), and the Editor of Surrogate modeling for high-frequency design: recent advances (World Scientific, 2022). Her research interests include simulation-driven design, design optimization, experiment design, control theory, modeling of microwave and antenna structures, numerical analysis. Since 2021, she consistently made the list of top 2% scientists by Stanford University in the field of Networking & Telecommunications. She published over 250 peer-reviewed research papers. Her h-index is 31 with over 3600 citations.
