1.Definitions and Basics of Deep Learning and Artificial Intelligence 2.Overview of Recent Advancements in DL and AI 3.Breaking the Curse of Dimensionality in Advances in Electromagnetics Design Through Optimization Empowered by Machine Learning 4.Artificial Neural Networks for Parametric Electromagnetic Modeling and Optimization 5.Advanced Neural Networks for Electromagnetic Modeling and Design 6.Generative Machine Learning for Photonic Design 7.Inverse Design of Electromagnetic Systems Using Deep Generative Neural Networks 8.Exhaustive Characterization of Metasurface Supercell Robustness Using Deep Learning 9.Machine Learning in Metasurfaces Design and Their Applications 10.Deep Learning for Metasurfaces and Metasurfaces for Deep Learning 11.Forward and Inverse Design of Artificial Electromagnetic Materials 12.Machine Learning-Assisted Optimization and its Application to Antenna and Array Designs 13.Analysis of Uniform and Non-Uniform Antenna Arrays Using Kernel Methods 14.Knowledge-based Globalized Optimization of High-frequency Structures Using Inverse Surrogates 15.Deep Learning for High Contrast Inverse Scattering of Electrically Large Structures 16.Radar Target Classification Using Deep Learning 17.Koopman Autoencoder for Physics-informed Machine Learning Based Reduced-order Kinetic Plasma Models Index

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