AI-assisted metaphotonics
人工智能辅助超光子学
AI支援メタフォトニクス
AI 보조 메타포토닉스
Metafotónica asistida por IA
La métaphotonique assistée par l'IA
ИИ-содействующая метафотоника
AI支援メタフォトニクス
AI 보조 메타포토닉스
Metafotónica asistida por IA
La métaphotonique assistée par l'IA
ИИ-содействующая метафотоника
Minsung Kang ¹, Seokju Choi ², Kaixi Fu ¹, Xiaoyuan Liu ³, Zhun Wei 魏准 ⁴, Lei Jin 晋蕾 ⁵, Hao Wang 王浩 ⁶ ⁷, Olivier J. F. Martin ³, Joel K. W. Yang ⁸, Sunae So ², Trevon Badloe ¹ ⁹ ¹⁰
¹ Department of Electronics and Information Engineering, Korea University, Sejong 30019, Republic of Korea
² Department of Control and Instrumentation Engineering, Korea University, Sejong 30019, Republic of Korea
³ Nanophotonics and Metrology Laboratory (NAM), Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne 1015, Switzerland
⁴ Innovation Institute of Electromagnetic Information and Electronics Integration, Zhejiang Key Laboratory of Intelligent – Electromagnetic Control and Advanced Electronic Integration, College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou 310017, China
中国 杭州 浙江大学信息科学与电子工程学院 电磁信息与电子集成创新研究所 全省电磁智能感控与先进电子集成重点实验室
⁵ Key Laboratory of RF Circuits & System of Ministry of Education, School of Electronics and Information, Hangzhou Dianzi University, Xiasha High Education Park, Hangzhou 310018, China
中国 杭州 下沙高教园区 杭州电子科技大学电子信息学院 射频电路与系统教育部重点实验室
⁶ School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
中国 北京 北京航空航天大学仪器科学与光电工程学院
⁷ Hangzhou International Innovation Institute, Beihang University, Hangzhou 311115, China
中国 杭州 北京航空航天大学杭州创新研究院
⁸ Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore
⁹ Division of Smart Energy Convergence Engineering, Korea University, Sejong 30019, Republic of Korea
¹⁰ Digital Healthcare Center, Sejong Institute for Business and Technology, Korea University, Sejong 30019, Republic of Korea
² Department of Control and Instrumentation Engineering, Korea University, Sejong 30019, Republic of Korea
³ Nanophotonics and Metrology Laboratory (NAM), Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne 1015, Switzerland
⁴ Innovation Institute of Electromagnetic Information and Electronics Integration, Zhejiang Key Laboratory of Intelligent – Electromagnetic Control and Advanced Electronic Integration, College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou 310017, China
中国 杭州 浙江大学信息科学与电子工程学院 电磁信息与电子集成创新研究所 全省电磁智能感控与先进电子集成重点实验室
⁵ Key Laboratory of RF Circuits & System of Ministry of Education, School of Electronics and Information, Hangzhou Dianzi University, Xiasha High Education Park, Hangzhou 310018, China
中国 杭州 下沙高教园区 杭州电子科技大学电子信息学院 射频电路与系统教育部重点实验室
⁶ School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China
中国 北京 北京航空航天大学仪器科学与光电工程学院
⁷ Hangzhou International Innovation Institute, Beihang University, Hangzhou 311115, China
中国 杭州 北京航空航天大学杭州创新研究院
⁸ Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore
⁹ Division of Smart Energy Convergence Engineering, Korea University, Sejong 30019, Republic of Korea
¹⁰ Digital Healthcare Center, Sejong Institute for Business and Technology, Korea University, Sejong 30019, Republic of Korea
Opto-Electronic Advances, 17 April 2026
Abstract
The convergence of artificial intelligence (AI) and metaphotonics is creating a new paradigm for controlling light-matter interactions. The synergy of AI's ability to learn complex relationships in multidimensional data and provide ultra-fast inference with the capacity of metaphotonics to engineer optical properties not found in nature is unlocking a new era in computational design, real-time control, and fully automated optical systems.
This review provides a comprehensive overview of state-of-the-art AI-driven approaches for metaphotonic systems. We focus on the solutions to real-world problems in accelerating metaphotonic simulations and inverse design, optical data characterization, and the development of fully integrated end-to-end AI-assisted metaphotonic systems. Finally, we provide our perspectives on the future research directions and emerging opportunities at the rapidly evolving intersection of metaphotonics and AI.
The convergence of artificial intelligence (AI) and metaphotonics is creating a new paradigm for controlling light-matter interactions. The synergy of AI's ability to learn complex relationships in multidimensional data and provide ultra-fast inference with the capacity of metaphotonics to engineer optical properties not found in nature is unlocking a new era in computational design, real-time control, and fully automated optical systems.
This review provides a comprehensive overview of state-of-the-art AI-driven approaches for metaphotonic systems. We focus on the solutions to real-world problems in accelerating metaphotonic simulations and inverse design, optical data characterization, and the development of fully integrated end-to-end AI-assisted metaphotonic systems. Finally, we provide our perspectives on the future research directions and emerging opportunities at the rapidly evolving intersection of metaphotonics and AI.
Reviews and Discussions