• Photonics Research
  • Vol. 9, Issue 8, 0800DLP1 (2021)
Li Gao1、5、*, Yang Chai2、6、*, Darko Zibar3、7、*, and Zongfu Yu4、8、*
Author Affiliations
  • 1Institute of Advanced Materials (IAM), and School of Materials Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210046, China
  • 2Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong, China
  • 3Department of Photonics Engineering, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark
  • 4Department of Electrical and Computer Engineering, University of Wisconsin, Madison, Wisconsin 53706, USA
  • 5e-mail: iamlgao@njupt.edu.cn
  • 6e-mail: ychai@polyu.edu.hk
  • 7e-mail: dazi@fotonik.dtu.dk
  • 8e-mail: zyu54@wisc.edu
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    The connection between Maxwell’s equations and neural networks opens unprecedented opportunities at the interface between photonics and deep learning. This feature issue highlights recent research progress at the interdisciplinary field of photonics and deep learning and provides an opportunity for different communities to exchange their ideas from different perspectives.

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    Li Gao, Yang Chai, Darko Zibar, Zongfu Yu. Deep learning in photonics: introduction[J]. Photonics Research, 2021, 9(8): 0800DLP1
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    Received: Apr. 22, 2021
    Accepted: --
    Posted: Apr. 22, 2021
    Published Online: Jul. 22, 2021
    The Author Email: Li Gao (iamlgao@njupt.edu.cn), Yang Chai (ychai@polyu.edu.hk), Darko Zibar (dazi@fotonik.dtu.dk), Zongfu Yu (zyu54@wisc.edu)