Kai Xu

71 papers receiving 839 citations

Peers

Kai Xu
Comparison fields: 5 of 92
  • Computer Vision and Pattern Recognition 505
  • Information Systems and Management 130
  • Signal Processing 140
  • Statistical and Nonlinear Physics 149
  • Computer Graphics and Computer-Aided Design 44
Replace Çağatay Turkay with:
Çağatay Turkay United Kingdom
Jörn Schneidewind Germany
Lucy Nowell United States
Robert Amar United States
Dominik Sacha Germany
T. J. Jankun-Kelly United States
S. Havre United States
Keith Andrews Austria
Michelle Q. Wang Baldonado United States
Geoffrey P. Ellis United Kingdom
Kai Xu relative to Çağatay Turkay United Kingdom Çağatay Turkay's profile →
Citations per field
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Çağatay Turkay · 1×
Citations per year

Countries citing papers authored by Kai Xu

Since Specialization
Citations

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

Fields of papers citing papers by Kai Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202081
2 201255
3 201554
4 202249
5 201538
6 200634
7
Visual analysis of network centralities
200632
8 201631
9 201328
10 201124
11 201421
12 200621
13
FlowRecommender: a workflow recommendation technique for process provenance
200920
14 202419
15 200719
16 200719
17 201518
18 201416
19 202216
20 201115

About Kai Xu

Kai Xu is a scholar working on Computer Vision and Pattern Recognition, Information Systems and Management, Statistical and Nonlinear Physics, Signal Processing and Computer Graphics and Computer-Aided Design, having authored 79 papers that have together received 882 indexed citations. Recurring topics across this work include Data Visualization and Analytics (42 papers), Scientific Computing and Data Management (17 papers), Complex Network Analysis Techniques (16 papers), Data Management and Algorithms (12 papers), Bioinformatics and Genomic Networks (8 papers), Computer Graphics and Visualization Techniques (6 papers), Research Data Management Practices (4 papers) and Gene expression and cancer classification (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (505 citations), Information Systems and Management (130 citations), Signal Processing (140 citations), Statistical and Nonlinear Physics (149 citations) and Computer Graphics and Computer-Aided Design (44 citations). Kai Xu has collaborated with scholars based in Australia, United Kingdom and China. Frequent co-authors include Phong Hai Nguyen, B. L. William Wong, Dirk Koschützki, Simon Attfield, Remco Chang, Seok-Hee Hong, Chris Rooney, John E. Wenskovitch, Marc Streit and Alvitta Ottley. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, IEEE Computer Graphics and Applications, Computer Graphics Forum, Information Visualization and Lecture notes in computer science.

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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