Jianshe Wu

2.2k total citations · 1 hit paper
75 papers, 1.7k citations indexed

About

Jianshe Wu is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Jianshe Wu has authored 75 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Statistical and Nonlinear Physics, 30 papers in Computer Networks and Communications and 26 papers in Artificial Intelligence. Recurrent topics in Jianshe Wu's work include Complex Network Analysis Techniques (29 papers), Opinion Dynamics and Social Influence (20 papers) and Nonlinear Dynamics and Pattern Formation (14 papers). Jianshe Wu is often cited by papers focused on Complex Network Analysis Techniques (29 papers), Opinion Dynamics and Social Influence (20 papers) and Nonlinear Dynamics and Pattern Formation (14 papers). Jianshe Wu collaborates with scholars based in China, United States and Montenegro. Jianshe Wu's co-authors include Licheng Jiao, Yutao Qi, Fang Liu, Xiaoliang Ma, Jianyong Sun, Weisheng Chen, Xiaohua Wang, Jianrui Chen, Yang Jiao and Fang Liu and has published in prestigious journals such as PLoS ONE, Scientific Reports and Expert Systems with Applications.

In The Last Decade

Jianshe Wu

73 papers receiving 1.7k citations

Hit Papers

MOEA/D with Adaptive Weight Adjustment 2013 2026 2017 2021 2013 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jianshe Wu China 22 818 677 575 509 144 75 1.7k
Carlos Cotta Spain 17 978 1.2× 440 0.6× 96 0.2× 211 0.4× 124 0.9× 112 1.8k
Chao Luo China 23 406 0.5× 160 0.2× 468 0.8× 339 0.7× 206 1.4× 111 1.7k
Nan Lu China 20 853 1.0× 473 0.7× 158 0.3× 432 0.8× 64 0.4× 74 1.7k
Qiang He China 23 384 0.5× 256 0.4× 327 0.6× 766 1.5× 90 0.6× 122 1.7k
Emmanuel Müller Germany 24 1.9k 2.3× 96 0.1× 359 0.6× 560 1.1× 45 0.3× 80 2.3k
Michèle Sébag France 24 1.0k 1.3× 461 0.7× 42 0.1× 323 0.6× 152 1.1× 86 1.7k
Mahantesh Halappanavar United States 16 330 0.4× 116 0.2× 314 0.5× 439 0.9× 28 0.2× 108 1.1k
Paola Flocchini Canada 26 213 0.3× 419 0.6× 233 0.4× 1.9k 3.7× 133 0.9× 144 2.4k
M. R. Meybodi Iran 20 629 0.8× 356 0.5× 43 0.1× 821 1.6× 72 0.5× 77 1.5k
Alexander L. Strehl United States 20 1.3k 1.6× 209 0.3× 175 0.3× 179 0.4× 345 2.4× 28 1.8k

Countries citing papers authored by Jianshe Wu

Since Specialization
Citations

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

Fields of papers citing papers by Jianshe Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jianshe Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Jianshe Wu. A scholar is included among the top collaborators of Jianshe Wu 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 Jianshe Wu. Jianshe Wu 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
1.
Sun, G. X., et al.. (2025). Community evolution prediction based on feature change patterns in social networks. Scientific Reports. 15(1). 14608–14608.
2.
Wu, Jianshe, et al.. (2025). HGphormer: Heterophilic Graph Transformer. Knowledge-Based Systems. 326. 114031–114031.
3.
Wu, Jianshe, et al.. (2024). FIAD: Graph anomaly detection framework based feature injection. Expert Systems with Applications. 259. 125216–125216. 2 indexed citations
4.
Jiao, Yang, Jianshe Wu, Xiang Peng, & Fang Wang. (2023). Link prediction from fusion information. Physica A Statistical Mechanics and its Applications. 618. 128694–128694. 3 indexed citations
5.
Jiao, Licheng, et al.. (2023). Community evolution prediction based on a self-adaptive timeframe in social networks. Knowledge-Based Systems. 275. 110687–110687. 3 indexed citations
6.
Wu, Jianshe, et al.. (2023). Multiple sparse graphs condensation. Knowledge-Based Systems. 278. 110904–110904. 9 indexed citations
7.
Jiao, Licheng, et al.. (2020). Multi-Resolution Prediction Model Based on Community Relevance for Missing Links Prediction. IEEE Access. 8. 113981–113993. 2 indexed citations
8.
Wu, Jianshe, et al.. (2019). Influence maximization based on the realistic independent cascade model. Knowledge-Based Systems. 191. 105265–105265. 21 indexed citations
9.
Wu, Jianshe, et al.. (2018). Endometrioid Adenocarcinoma With Solitary Metastasis to the Appendix, Mimicking Primary Appendiceal Adenocarcinoma: A Case Report and Literature Review. International Journal of Gynecological Pathology. 38(4). 393–396. 2 indexed citations
10.
Xu, Xiaoya, Bo Liu, Jianshe Wu, & Licheng Jiao. (2017). Link prediction in complex networks via matrix perturbation and decomposition. Scientific Reports. 7(1). 14724–14724. 8 indexed citations
11.
Jiao, Licheng, et al.. (2017). A group evolving-based framework with perturbations for link prediction. Physica A Statistical Mechanics and its Applications. 475. 117–128. 11 indexed citations
12.
Wu, Jianshe, Fang Wang, & Xiang Peng. (2015). Automatic network clustering via density-constrained optimization with grouping operator. Applied Soft Computing. 38. 606–616. 14 indexed citations
13.
Jiao, Licheng, et al.. (2015). A two-phase knowledge based hyper-heuristic scheduling algorithm in cellular system. Knowledge-Based Systems. 88. 244–252. 6 indexed citations
14.
Wu, Jianshe & Yang Jiao. (2014). Clustering dynamics of complex discrete-time networks and its application in community detection. Chaos An Interdisciplinary Journal of Nonlinear Science. 24(3). 33104–33104. 25 indexed citations
15.
Ma, Xiaoliang, Fang Liu, Yutao Qi, et al.. (2014). MOEA/D with opposition-based learning for multiobjective optimization problem. Neurocomputing. 146. 48–64. 67 indexed citations
16.
Gou, Shuiping, Yueyue Wang, Yong Peng, et al.. (2013). CT Image Sequence Restoration Based on Sparse and Low-Rank Decomposition. PLoS ONE. 8(9). e72696–e72696. 6 indexed citations
17.
Wu, Jianshe, Licheng Jiao, Chao Jin, et al.. (2012). Overlapping community detection via network dynamics. Physical Review E. 85(1). 16115–16115. 49 indexed citations
18.
Wu, Jianshe, et al.. (2012). Simple harmonic oscillator immune optimization algorithm for solving vertical handoff decision problem in heterogeneous wireless network. Acta Physica Sinica. 61(9). 96401–96401. 5 indexed citations
19.
Chen, Weisheng, Licheng Jiao, & Jianshe Wu. (2010). Globally stable adaptive robust tracking control using RBF neural networks as feedforward compensators. Neural Computing and Applications. 21(2). 351–363. 44 indexed citations
20.
Wu, Jianshe & Licheng Jiao. (2007). Synchronization in complex delayed dynamical networks with nonsymmetric coupling. Physica A Statistical Mechanics and its Applications. 386(1). 513–530. 74 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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