Shaolin Tan

612 total citations
40 papers, 436 citations indexed

About

Shaolin Tan is a scholar working on Sociology and Political Science, Computer Networks and Communications and Statistical and Nonlinear Physics. According to data from OpenAlex, Shaolin Tan has authored 40 papers receiving a total of 436 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Sociology and Political Science, 13 papers in Computer Networks and Communications and 13 papers in Statistical and Nonlinear Physics. Recurrent topics in Shaolin Tan's work include Evolutionary Game Theory and Cooperation (19 papers), Evolution and Genetic Dynamics (12 papers) and Game Theory and Applications (11 papers). Shaolin Tan is often cited by papers focused on Evolutionary Game Theory and Cooperation (19 papers), Evolution and Genetic Dynamics (12 papers) and Game Theory and Applications (11 papers). Shaolin Tan collaborates with scholars based in China, Australia and Hong Kong. Shaolin Tan's co-authors include Jinhu Lü, Yaonan Wang, David J. Hill, Yao Chen, Henghui Zhu, Wenwu Yu, Zongli Lin, Athanasios V. Vasilakos, Yao Chen and Guanrong Chen and has published in prestigious journals such as IEEE Transactions on Automatic Control, Scientific Reports and Automatica.

In The Last Decade

Shaolin Tan

31 papers receiving 410 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Shaolin Tan China	11	207	141	138	88	83	40	436
James R. Riehl United States	10	110 0.5×	150 1.1×	89 0.6×	61 0.7×	63 0.8×	26	379
Chun-Xiao Jia China	16	88 0.4×	183 1.3×	281 2.0×	55 0.6×	83 1.0×	39	568
Peilian Guo China	10	77 0.4×	86 0.6×	39 0.3×	72 0.8×	76 0.9×	18	378
Shihua Fu China	11	49 0.2×	97 0.7×	33 0.2×	73 0.8×	93 1.1×	64	386
B.-H. Wang China	7	66 0.3×	135 1.0×	213 1.5×	44 0.5×	73 0.9×	8	363
Xiao Luo China	15	294 1.4×	25 0.2×	380 2.8×	114 1.3×	55 0.7×	35	710
Xuehui Mei China	9	100 0.5×	89 0.6×	162 1.2×	73 0.8×	12 0.1×	22	312
Daan Bloembergen Netherlands	7	46 0.2×	91 0.6×	22 0.2×	18 0.2×	35 0.4×	24	288
Shuyue Hu China	8	35 0.2×	99 0.7×	36 0.3×	18 0.2×	28 0.3×	26	258
Emanuele Cozzo Spain	11	98 0.5×	63 0.4×	360 2.6×	33 0.4×	13 0.2×	20	487

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-authorship network of co-authors of Shaolin Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Shaolin Tan. A scholar is included among the top collaborators of Shaolin Tan 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 Shaolin Tan. Shaolin Tan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Tao, Ye, et al.. (2025). LCWF: Low-Overhead Collaborative WiFi Fingerprint Localization Considering Devices Heterogeneity. IEEE Transactions on Network Science and Engineering. 13. 2838–2851.

Tan, Shaolin, et al.. (2025). Backtracing Byzantine attacks in distributed average consensus networks: A gated graph neural network approach with graph reconstruction. Engineering Applications of Artificial Intelligence. 156. 111093–111093. 1 indexed citations

Liu, Hui, Xiaoqun Wu, Shaolin Tan, et al.. (2025). Optimizing Superdiffusion of Multiplex Networks Based on Spectral Graph Theory. IEEE Transactions on Systems Man and Cybernetics Systems. 55(12). 9043–9056.

Tan, Shaolin. (2025). A Distributed Nesterov’s Approach for Fast Nash Equilibrium Seeking in Noncooperative Games. Journal of Systems Science and Complexity. 38(5). 1987–2006.

Tan, Shaolin, et al.. (2024). A timestamp-based log-linear algorithm for solving locally-informed multi-agent finite games. Expert Systems with Applications. 249. 123677–123677.

Liu, Nian, et al.. (2024). Vulnerability of AND/OR logic networks under cascading failures. Physics Letters A. 525. 129913–129913.

Tan, Shaolin, et al.. (2024). A timestamp-based Nesterov’s accelerated projected gradient method for distributed Nash equilibrium seeking in monotone games. Systems & Control Letters. 194. 105966–105966. 1 indexed citations

Wang, Jiakai, et al.. (2024). Adversarial Examples Against WiFi Fingerprint-Based Localization in the Physical World. IEEE Transactions on Information Forensics and Security. 19. 8457–8471. 3 indexed citations

Tao, Ye, et al.. (2024). CBWF+: Collaboratively Enhanced Lightweight Circular-Boundary-Based WiFi Fingerprinting. IEEE Internet of Things Journal. 1–1. 3 indexed citations

10.

Tan, Shaolin. (2023). A timestamp-based projected gradient play for distributed Nash equilibrium seeking in monotone games. Automatica. 160. 111419–111419. 8 indexed citations

11.

Tan, Shaolin, et al.. (2023). A Signed Subgraph Encoding Approach via Linear Optimization for Link Sign Prediction. IEEE Transactions on Neural Networks and Learning Systems. 35(10). 14659–14670. 2 indexed citations

12.

Tan, Shaolin, et al.. (2023). On the convergence of distributed projected gradient play with heterogeneous learning rates in monotone games. Systems & Control Letters. 182. 105654–105654.

13.

Tan, Shaolin, et al.. (2021). Elementary Subgraph Features for Link Prediction With Neural Networks. IEEE Transactions on Knowledge and Data Engineering. 35(4). 3822–3831. 10 indexed citations

14.

Tan, Shaolin & Yaonan Wang. (2021). A payoff-based learning approach for Nash equilibrium seeking in continuous potential games. Neurocomputing. 468. 431–440. 10 indexed citations

15.

Tan, Shaolin & Jinhu Lü. (2016). An evolutionary game approach for determination of the structural conflicts in signed networks. Scientific Reports. 6(1). 22022–22022. 14 indexed citations

16.

Tan, Shaolin, Yaonan Wang, Yao Chen, & Zhen Wang. (2016). Evolutionary Dynamics of Collective Behavior Selection and Drift: Flocking, Collapse, and Oscillation. IEEE Transactions on Cybernetics. 47(7). 1694–1705. 22 indexed citations

17.

Tan, Shaolin, Yaonan Wang, & Jinhu Lü. (2016). Analysis and Control of Networked Game Dynamics via A Microscopic Deterministic Approach. IEEE Transactions on Automatic Control. 61(12). 4118–4124. 32 indexed citations

18.

Tan, Shaolin, Jinhu Lü, & Zongli Lin. (2016). Emerging Behavioral Consensus of Evolutionary Dynamics on Complex Networks. SIAM Journal on Control and Optimization. 54(6). 3258–3272. 38 indexed citations

19.

Tan, Shaolin & Jinhu Lü. (2014). Characterizing the effect of population heterogeneity on evolutionary dynamics on complex networks. Scientific Reports. 4(1). 5034–5034. 28 indexed citations

20.

Tan, Shaolin, et al.. (2014). Strategy Selection in Evolutionary Game Dynamics on Group Interaction Networks. Bulletin of Mathematical Biology. 76(11). 2785–2805. 8 indexed citations

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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