Emerging role of machine learning in light-matter interaction

Jiajia Zhou*, Bolong Huang, Zheng Yan, Jean-Claude G. Bünzli

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

71 Citations (Scopus)
13 Downloads (CityUHK Scholars)

Abstract

Machine learning has provided a huge wave of innovation in multiple fields, including computer vision, medical diagnosis, life sciences, molecular design, and instrumental development. This perspective focuses on the implementation of machine learning in dealing with light-matter interaction, which governs those fields involving materials discovery, optical characterizations, and photonics technologies. We highlight the role of machine learning in accelerating technology development and boosting scientific innovation in the aforementioned aspects. We provide future directions for advanced computing techniques via multidisciplinary efforts that can help to transform optical materials into imaging probes, information carriers and photonics devices. © The Author(s) 2019.
Original languageEnglish
Article number84
JournalLight: Science & Applications
Volume8
Online published11 Sept 2019
DOIs
Publication statusPublished - 2019
Externally publishedYes

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

Fingerprint

Dive into the research topics of 'Emerging role of machine learning in light-matter interaction'. Together they form a unique fingerprint.

Cite this