Surface plasmons (SPs) are collective excitations of conduction electrons at the metal-dielectric interface, which significantly enhance light-matter interactions, giving rise to novel physical phenomena and fostering the development of innovative applications. This field currently represents a prominent research focus in condensed matter physics and nano-optics. Recently, the team led by Prof. Zheyu Fang at Peking University, was invited to author a review paper entitled "Dual views on plasmonics: from near-field optics to electron nanoscopy", which was published in Issue 2 Volume 4 of Photonics Insights in 2025. (Yuxiang Chen, Han Zhang, Zongkun Zhang, Xing Zhu, Zheyu Fang. Duel views of plasmonics: from near-field optics to electron nanoscopy[J]. Photonics Insights, 2025, 4(2): R04)

Recently, a review paper titled "Comprehensive review on developments of synthetic dimensions" was published in the Issue 2 of Photonics Insights, 2025. (Danying Yu, Wange Song, Luojia Wang, Rohith Srikanth, Sashank Kaushik Sridhar, Tao Chen, Chenxi Huang, Guangzhen Li, Xin Qiao, Xiaoxiong Wu, Zhaohui Dong, Yanyan He, Meng Xiao, Xianfeng Chen, Avik Dutt, Bryce Gadway, Luqi Yuan. Comprehensive review on developments of synthetic dimensions [J]. Photonics Insights, 2025, 4(2): R06.)

The advent of deep integration and development in the domains of information technology and computational science has precipitated a paradigm shift in modern imaging technology, transitioning it from a device-driven model to one that is increasingly led by information transmission. Consequently, computational imaging has emerged as a paradigm shift, transcending the limitations of conventional technological approaches by establishing an interdisciplinary research framework that integrates multi-dimensional physical information perception and computational information interpretation. Prof. Fei Liu of Xidian University was recently invited by the editor-in-chief of Photonics Insights to co-author a paper entitled "Revolutionizing Optical Imaging: Computational imaging via deep learning". The project is being led by Prof. Chao Zuo of Nanjing University of Science and Technology, Prof. Zihan Geng of Tsinghua University, and Postdoc Yi Wei of MIT.