Tao Gui

5.4k citations
152 papers · 2.9k · h-index 26

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Text and Document Classification Technologies
    • Advanced Text Analysis Techniques
    • Optical Network Technologies
    • Advanced Photonic Communication Systems
    • Photonic and Optical Devices

Papers in

Tao Gui

141 papers receiving 2.8k citations

Peers

Tao Gui
Comparison fields: 5 of 125
  • Artificial Intelligence 1.3k
  • Electrical and Electronic Engineering 1.3k
  • Atomic and Molecular Physics, and Optics 452
  • Management Science and Operations Research 148
  • Applied Psychology 45
Replace Nan Hua with:
Nan Hua China
Yuhua Li China
Wenqiang Lei China
Yohei Murakami Japan
Liang Ding China
Xianwei Zhou China
Haifeng Sun China
Quan Zhang China
Chong Chen China
Kyung-Joong Kim South Korea
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Citations per field
00.5×10×16.1×
Nan Hua · 1×
Citations per year

Countries citing papers authored by Tao Gui

Since Specialization
Citations

This map shows the geographic impact of Tao Gui's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tao Gui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tao Gui more than expected).

Fields of papers citing papers by Tao Gui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tao Gui. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tao Gui. The network helps show where Tao Gui may publish in the future.

Co-authors

The 25 scholars most cited alongside Tao Gui, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tao Gui Line = papers co-authored together Tao Gui links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 152 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015262
2 2021192
3 2019182
4 2019176
5 2020131
6 201992
7 201991
8 201486
9 201585
10 201778
11 202178
12 202273
13 201768
14 201757
15 202350
16 202249
17 201848
18 201344
19 202444
20 202143

About Tao Gui

Tao Gui is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics, Computer Vision and Pattern Recognition and Biomedical Engineering, having authored 152 papers that have together received 2.9k indexed citations. Recurring topics across this work include Optical Network Technologies (52 papers), Topic Modeling (49 papers), Advanced Photonic Communication Systems (42 papers), Natural Language Processing Techniques (38 papers), Photonic and Optical Devices (24 papers), Advanced Fiber Laser Technologies (20 papers), Multimodal Machine Learning Applications (14 papers) and Sentiment Analysis and Opinion Mining (10 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Electrical and Electronic Engineering (1.3k citations), Atomic and Molecular Physics, and Optics (452 citations), Management Science and Operations Research (148 citations) and Applied Psychology (45 citations). Tao Gui has collaborated with scholars based in China, Hong Kong and Australia. Frequent co-authors include Qi Zhang, Chao Lü, Alan Pak Tao Lau, Xuanjing Huang, Minlong Peng, Ruotian Ma, Kangping Zhong, Gai Zhou, Yu–Gang Jiang and Yicheng Zou. Their work appears in journals such as Optics Express, Journal of Lightwave Technology, IEEE Photonics Technology Letters, IEEE photonics journal and Applied Thermal Engineering.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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