Kaijun Wu

707 citations
64 papers · 464 · h-index 10

Impact in

Papers in

Kaijun Wu

56 papers receiving 445 citations

Peers

Kaijun Wu
Comparison fields: 5 of 65
  • Statistical and Nonlinear Physics 135
  • Computer Networks and Communications 137
  • Computer Vision and Pattern Recognition 84
  • Cognitive Neuroscience 74
  • Electrical and Electronic Engineering 174
Replace Yoko Uwate with:
Yoko Uwate Japan
Duqu Wei China
Frank Z. Wang United Kingdom
Evangelos Pikasis Greece
Farhan Qamar Pakistan
Joseph Yves Effa Cameroon
A. Lozowski United States
Zhisen Wang China
Valerii Y. Ostrovskii Russia
Тимур Каримов Russia
Kaijun Wu relative to Yoko Uwate Japan Yoko Uwate's profile →
Citations per field
00.5×6.5×
Yoko Uwate · 1×
Citations per year

Countries citing papers authored by Kaijun Wu

Since Specialization
Citations

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

Fields of papers citing papers by Kaijun Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 64 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004118
2 201854
3 201545
4 201619
5 202314
6 202112
7 202112
8 201811
9 201110
10 20219
11 20228
12 20228
13 20218
14 20247
15 20227
16 20247
17 20127
18 20236
19 20206
20 20116

About Kaijun Wu

Kaijun Wu is a scholar working on Computer Networks and Communications, Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 64 papers that have together received 464 indexed citations. Recurring topics across this work include stochastic dynamics and bifurcation (14 papers), Neural dynamics and brain function (12 papers), Nonlinear Dynamics and Pattern Formation (10 papers), Network Security and Intrusion Detection (5 papers), Anomaly Detection Techniques and Applications (5 papers), Internet Traffic Analysis and Secure E-voting (4 papers), Video Surveillance and Tracking Methods (3 papers) and Cloud Computing and Resource Management (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (135 citations), Computer Networks and Communications (137 citations), Computer Vision and Pattern Recognition (84 citations), Cognitive Neuroscience (74 citations) and Electrical and Electronic Engineering (174 citations). Kaijun Wu has collaborated with scholars based in China, United Kingdom and Taiwan. Frequent co-authors include Shigeru Suzuki, Shiyi Cao, Y. Hibino, Yang Wang, C.R. Doerr, Jay N. Damask, Jenhui Chen, Pengfei Xie, G. T. Harvey and Qinghua Hu. Their work appears in journals such as Applied Sciences, Computational Intelligence and Neuroscience, Scientific Reports, IEEE Transactions on Consumer Electronics and Electronics.

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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