AI-Driven Metasurfaces, Antennas, and Wireless Systems

Dear Colleagues,

Artificial intelligence (AI) is reshaping the design paradigm of metasurfaces, antennas, and wireless systems. Conventional electromagnetic design relies heavily on iterative full-wave simulations and expert-driven optimization, which are computationally intensive and time-consuming. AI-driven approaches, including surrogate modeling, inverse design, generative methods, and intelligent optimization, provide new opportunities to significantly accelerate the design process while enhancing performance, adaptability, and system-level integration. By combining data-driven techniques with electromagnetic theory, researchers can move beyond traditional trial-and-error methodologies toward automated and intelligent electromagnetic engineering.

This Special Issue aims to explore the transformative role of AI in metasurface and antenna design as well as next-generation wireless systems. We welcome original research and review articles that develop innovative AI methodologies and validate them through rigorous simulations or experimental demonstrations to ensure practical applicability and reproducibility.

Topics include, but are not limited to:

• AI-driven metasurface and antenna design;
• Surrogate modeling for electromagnetics;
• Inverse and generative electromagnetic design;
• Physics-informed learning methods;
• Intelligent optimization techniques;
• Smart and reconfigurable wireless systems;
• AI-enabled RF and system-level design.

We look forward to receiving your contributions.

Dr. Zhaohui Wei
Dr. Zhao Zhou
Dr. Ming Shen
Guest Editors

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