Kai Shen

50 total papers · 915 total citations
32 papers, 561 citations indexed

About

Kai Shen is a scholar working on Computer Networks and Communications, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Kai Shen has authored 32 papers receiving a total of 561 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Networks and Communications, 9 papers in Information Systems and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Kai Shen's work include Parallel Computing and Optimization Techniques (6 papers), Distributed systems and fault tolerance (5 papers) and Distributed and Parallel Computing Systems (5 papers). Kai Shen is often cited by papers focused on Parallel Computing and Optimization Techniques (6 papers), Distributed systems and fault tolerance (5 papers) and Distributed and Parallel Computing Systems (5 papers). Kai Shen collaborates with scholars based in China, United States and Canada. Kai Shen's co-authors include Qiaoling Hu, Tao Yang, Min Fan, Lingkun Chu, Ming Zhong, Hong Tang, Hong Tang, Tao Yang, Xiangmin Jiao and 李浩 Li Hao and has published in prestigious journals such as Nature Communications, Physical review. B, Condensed matter and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Kai Shen

31 papers receiving 532 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Kai Shen 237 110 105 76 56 32 561
Ying Lu 188 0.8× 74 0.7× 53 0.5× 58 0.8× 22 0.4× 49 508
Qikun Zhang 194 0.8× 138 1.3× 72 0.7× 11 0.1× 36 0.6× 31 573
Zhong Li 239 1.0× 57 0.5× 53 0.5× 13 0.2× 49 0.9× 49 577
Nanxi Chen 195 0.8× 102 0.9× 90 0.9× 5 0.1× 63 1.1× 29 559
Dan Xu 320 1.4× 79 0.7× 31 0.3× 10 0.1× 67 1.2× 48 579
Zhen Chen 288 1.2× 157 1.4× 15 0.1× 77 1.0× 22 0.4× 56 606
Xiaokuan Zhang 186 0.8× 184 1.7× 7 0.1× 94 1.2× 28 0.5× 45 698
Yu Qin 97 0.4× 144 1.3× 21 0.2× 73 1.0× 42 0.8× 50 566
Yuanqiang Liu 124 0.5× 105 1.0× 68 0.6× 21 0.3× 55 1.0× 26 583
Yuandou Wang 153 0.6× 139 1.3× 156 1.5× 7 0.1× 81 1.4× 37 555

Countries citing papers authored by Kai Shen

Since Specialization
Citations

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

Fields of papers citing papers by Kai Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kai Shen

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

All Works

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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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