Shaolin Tan

629 citations
41 papers · 449 · h-index 12

Impact in

Papers in

Shaolin Tan

33 papers receiving 422 citations

Peers

Shaolin Tan
Comparison fields: 5 of 51
  • Statistical and Nonlinear Physics 143
  • Computer Networks and Communications 210
  • Management Science and Operations Research 72
  • Modeling and Simulation 16
  • Public Health, Environmental and Occupational Health 90
Replace James R. Riehl with:
James R. Riehl United States
Xiao Luo China
Shaoting Tang China
B.-H. Wang China
Peilian Guo China
S. Rasoul Etesami United States
Shihua Fu China
Zhenghong Deng China
Shuyue Hu China
Xuehui Mei China
Shaolin Tan relative to James R. Riehl United States James R. Riehl's profile →
Citations per field
00.5×5.3×
James R. Riehl · 1×
Citations per year

Countries citing papers authored by Shaolin Tan

Since Specialization
Citations

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

Fields of papers citing papers by Shaolin Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shaolin Tan. 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 Shaolin Tan. The network helps show where Shaolin Tan may publish in the future.

Co-authors

The 25 scholars most cited alongside Shaolin Tan, 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 Shaolin Tan Line = papers co-authored together Shaolin Tan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201665
2 201447
3 201638
4 201632
5 201431
6 202130
7 201428
8 201622
9 201920
10 201319
11 201615
12 202111
13 202110
14 202210
15 20229
16 20148
17 20238
18 20228
19 20125
20 20115

About Shaolin Tan

Shaolin Tan is a scholar working on Sociology and Political Science, Statistical and Nonlinear Physics, Computer Networks and Communications, Genetics and Management Science and Operations Research, having authored 41 papers that have together received 449 indexed citations. Recurring topics across this work include Evolutionary Game Theory and Cooperation (20 papers), Evolution and Genetic Dynamics (12 papers), Game Theory and Applications (11 papers), Opinion Dynamics and Social Influence (10 papers), Mathematical and Theoretical Epidemiology and Ecology Models (9 papers), Distributed Control Multi-Agent Systems (9 papers), Complex Network Analysis Techniques (8 papers) and Advanced Graph Neural Networks (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (143 citations), Computer Networks and Communications (210 citations), Management Science and Operations Research (72 citations), Modeling and Simulation (16 citations) and Public Health, Environmental and Occupational Health (90 citations). Shaolin Tan has collaborated with scholars based in China, Australia and Hong Kong. Frequent co-authors include Jinhu Lü, Yaonan Wang, David J. Hill, Yao Chen, Wenwu Yu, Henghui Zhu, Zongli Lin, Athanasios V. Vasilakos, Yao Chen and Guanrong Chen. Their work appears in journals such as IEEE Transactions on Systems Man and Cybernetics Systems, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Information Forensics and Security, IEEE Transactions on Cybernetics and Automatica.

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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