Year
Month
(Peer-Reviewed) AI-assisted metaphotonics
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
Opto-Electronic Advances, 2026-04-17
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.
AI-assisted metaphotonics_1
AI-assisted metaphotonics_2
AI-assisted metaphotonics_3
  • Halide perovskite-based metasurfaces: structure design, performance regulation, and optoelectronic applications
  • Junxue Liu, Ying Su, Zibo Gao, Yinghan Li, Jingyuan Jia, Dequn Zhang, Yijing Mao, Tun Cao
  • Opto-Electronic Manufacturing
  • 2026-09-25
  • Electrically switchable bright-field and interference-synthesized edge-enhanced imaging with a polarization-multiplexed metalens
  • Xiaotong Li, Junhwa Seong, Yeseul Kim, Kwang-Suk Oh, Shiqi Hu, Le Dai, Harit Keawmuang, Beomha Yang, Minseok Choi, Youngsun Jeon, Cherry Park, Weiyan Li, Tianxu Jia, Han Zhu, Xiaodong Cai, Qi Zheng, Jinhui Shi, Young-Ki Kim, Yuchuan Shao, Trevon Badloe, Junsuk Rho
  • Opto-Electronic Science
  • 2026-09-20
  • Multiphysics optimization framework for high-power fiber amplifiers
  • Wei Liu, Zan Cheng, Pengfei Ma, Yisha Chen, Huan Yang, Zhiyong Pan, Zefeng Wang, Jinbao Chen
  • Opto-Electronic Science
  • 2026-09-20
  • 3D-printed copper water cooling system assisted fabrication of 10.6-μm high-power CO₂ laser resistance reflectors
  • Hongfei Jiao, Binbin Jiang, Xinshang Niu, Yifan Wang, Dongdong Li, Jun Yu, Xiaochuan Ji, Jingjing Xia, Jinlong Zhang, Xinbin Cheng, Zhanshan Wang
  • Opto-Electronic Advances
  • 2026-09-15
  • Pixel-controlled programmable metasurface as phase-type spatial terahertz modulator
  • Guibin Li, Guanyi Li, Zehao He, Xinke Wang, Peter J. Klar, He Ma, Yan Zhang
  • Opto-Electronic Advances
  • 2026-09-15
  • Spatiotemporal beam stirring in a multicore fiber
  • Alena Y. Kolesnikova, Mikhail D. Gervaziev, Nikita V. Bochkarev, Denis S. Kharenko, Evgeniy V. Podivilov, Sergey A. Babin
  • Opto-Electronic Advances
  • 2026-09-15
  • Ultrafast all-optical modulation of wide-bandwidth pulses enabled by silicon-metasurfaces
  • Kaloyan Georgiev, Khosro Zangeneh Kamali, Anton A. Trifonov, Giulia Crotti, Lyuben Petrov, Stefan Georgiev, Hristo Iliev, Lei Xu, Unai Arregui Leon, Mohsen Rahmani, Giuseppe Della Valle, Ivan Buchvarov, Dragomir Neshev
  • Opto-Electronic Advances
  • 2026-09-15
  • Physics-informed neural fields enable blind aberration correction for partially coherent quantitative phase imaging
  • Shun Zhou, Xingyu Huang, Linpeng Lu, Habib Ullah, Kaiyu Du, Maciej Trusiak, Malgorzata Kujawinska, Yuzhen Zhang, Yao Fan, Qian Chen, Qinrong Zhang, Chao Zuo
  • Opto-Electronic Science
  • 2026-08-26
  • Programmable directional photonic spiking neuron based on a non-Hermitian silicon microresonator
  • Stefano Biasi, Bülent Aslan, Stefano Gretter, Davide Olivieri, Alessandro Foradori, Riccardo Franchi, Lorenzo Pavesi
  • Opto-Electronic Science
  • 2026-08-26
  • Mutual empowerment of artificial intelligence and metasurfaces: intelligent nanophotonics and optical intelligence
  • Yu Zhao, Zile Li, Yongquan Zeng, Shaohua Yu, Guoxing Zheng
  • Opto-Electronic Science
  • 2026-08-26



  • Polarization-guided diffusion prior for eyeglass reflection removal                                Interpretable low-dose CT enhancement via multi-Gaussian cluster variance reduction
    About
    |
    Contact
    |
    Copyright © PubCard