Gui-Bin Chen

924 total citations
32 papers, 662 citations indexed

About

Gui-Bin Chen is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Cognitive Neuroscience. According to data from OpenAlex, Gui-Bin Chen has authored 32 papers receiving a total of 662 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Artificial Intelligence, 17 papers in Atomic and Molecular Physics, and Optics and 3 papers in Cognitive Neuroscience. Recurrent topics in Gui-Bin Chen's work include Quantum Computing Algorithms and Architecture (18 papers), Quantum Information and Cryptography (18 papers) and Quantum Mechanics and Applications (15 papers). Gui-Bin Chen is often cited by papers focused on Quantum Computing Algorithms and Architecture (18 papers), Quantum Information and Cryptography (18 papers) and Quantum Mechanics and Applications (15 papers). Gui-Bin Chen collaborates with scholars based in China, Australia and Singapore. Gui-Bin Chen's co-authors include Zhenchang Xing, Deheng Ye, Xiaowei Li, You-Bang Zhan, Erik Cambria, Jieshan Chen, Peng‐Cheng Ma, Bowen Xu, Shanping Li and Xin Xia and has published in prestigious journals such as Expert Systems with Applications, Sensors and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Gui-Bin Chen

30 papers receiving 627 citations

Peers

Gui-Bin Chen
Comparison fields: 5 of 56
  • Artificial Intelligence 466
  • Information Systems 182
  • Atomic and Molecular Physics, and Optics 160
  • Computer Networks and Communications 58
  • Computer Vision and Pattern Recognition 48
Replace Xiaolin Jia with:
Xiaolin Jia China
Zhipeng Huang China
Ruijin Wang China
Gilles Dowek France
Johanna Barzen Germany
Wolfgang Menzel Germany
Xiaolin Jia China View profile →
Citations per field, relative to Gui-Bin Chen
Gui-Bin Chen · 1×
Citations per year, relative to Gui-Bin Chen
Gui-Bin Chen · 1×

Countries citing papers authored by Gui-Bin Chen

Since Specialization
Citations

This map shows the geographic impact of Gui-Bin Chen'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 Gui-Bin Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gui-Bin Chen more than expected).

Fields of papers citing papers by Gui-Bin Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gui-Bin Chen. 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 Gui-Bin Chen. The network helps show where Gui-Bin Chen may publish in the future.

Co-authorship network of co-authors of Gui-Bin Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Gui-Bin Chen. A scholar is included among the top collaborators of Gui-Bin Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gui-Bin Chen. Gui-Bin Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 4
3 14
4 0
5 9
6 21
7 27
8 3
9 31
10 1
11 6
12 7
13 19
14 177
15 21
16 1
17 110
18 3
19 6
20 38

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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