Year
Month
(Peer-Reviewed) AI-assisted metaphotonics
Minsung Kang ¹, Seokju Choi ², Kaixi Fu ¹, Xiaoyuan Liu ³, Zhun Wei ⁴, Lei Jin ⁵, Hao Wang 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
  • Soft chiral superstructure enabled dynamic polychromatic holography
  • Chun-Ting Xu, Lu Li, Quan-Ming Chen, Guang-Yao Wang, Wei Hu
  • Opto-Electronic Advances
  • 2026-02-12
  • Millisecond-level electrically switchable metalens for adaptive rotational depth mapping and diffraction-limited imaging
  • Yeseul Kim, Jihae Lee, Won-Sik Kim, Hyeonsu Heo, Dongmin Jeon, Beomha Yang, Xiaotong Li, Harit Keawmuang, Shiqi Hu, Young-Ki Kim, Trevon Badloe, Junsuk Rho
  • Opto-Electronic Advances
  • 2026-02-12
  • Ambient-energy-driven space-time-coding metasurface for space-frequency-division multiplexing wireless communications
  • Han Wei Tian, Chao Song, Dong Jie Wang, Qian Zhu, Tie Jun Cui, Wei Xiang Jiang
  • Opto-Electronic Advances
  • 2026-02-12
  • Ultra-sensitive multi-band infrared polarization photodetector based on 1T'-MoTe₂/2H-MoTe₂ van der Waals heterostructure
  • Yuting Pan, Lidan Lu, Bofei Zhu, Chunhua An, Jing Yu, Guanghui Ren, Jian Zhen Ou, Mingli Dong, Zheng You, Lianqing Zhu
  • Opto-Electronic Advances
  • 2026-02-09
  • Tunable compound eyes with coaxial lens-on-lens ommatidia for cooperative bi-focal imaging
  • Zhi-Juan Sun, Wei-Jian Zhong, Qing Cai, Yi-Fan Lu, Chang-Xu Li, Dong-Dong Han, Yong-Lai Zhang
  • Opto-Electronic Advances
  • 2026-02-09
  • High-efficiency infrared upconversion imaging with nonlinear silicon metasurfaces empowered by quasi-bound states in the continuum
  • Tingting Liu, Jumin Qiu, Meibao Qin, Xu Tu Huifu Qiu, Feng Wu, Tianbao Yu, Qiegen Liu, Shuyuan Xiao
  • Opto-Electronic Advances
  • 2026-01-29
  • Timeshare surface-enhanced Raman scattering platform with sensitive and quantitative mode
  • Qianqian Ding, Xueyan Chen, Yunlu Jia, Hong Liu, Xiaochen Zhang, Ningtao Cheng, Shikuan Yang
  • Opto-Electronic Advances
  • 2026-01-27
  • Electric-field-induced second-harmonic generation
  • Hangkai Fan, Alexey Proskurin, Mingzhao Song, Andrey Bogdanov
  • Opto-Electronic Advances
  • 2026-01-27
  • Fiber-optic microstructured sensors based on abrupt field patterns: theory, fabrication, and applications
  • Yuxuan Yi, Wanlai Zhu, Zao Yi, Zigang Zhou, Shubo Cheng, Majid Niaz Akhtar, Sohail Ahmad
  • Opto-Electronic Science
  • 2026-01-23
  • Integrated metasurface-freeform system enabled multi-focal planes augmented reality display
  • Shifei Zhang, Lina Gao, Yidan Zhao, Yongdong Wang, Bo Wang, Junjie Li, Jiaxi Duan, Dewen Cheng, Cheng-Wei Qiu, Yongtian Wang, Tong Yang, Lingling Huang
  • Opto-Electronic Science
  • 2026-01-23
  • Decoding subject-invariant emotional information from cardiac signals detected by photonic sensing system
  • Yukun Long, Rui Min Kun Xiao, Zhuo Wang, Lanfang Liu, Yifan Sun, Xiaoli Li, Zhaohui Li, Zeev Zalevsky
  • Opto-Electronic Technology
  • 2025-12-25
  • Integrated photonic synapses, neurons, memristors, and neural networks for photonic neuromorphic computing
  • Shufei Han, Weihong Shen, Min Gu, Qiming Zhang
  • Opto-Electronic Technology
  • 2025-12-25



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