Kaixuan Chen

43 total papers · 2.2k total citations
20 papers, 1.4k citations indexed

About

Kaixuan Chen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Kaixuan Chen has authored 20 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 7 papers in Cognitive Neuroscience. Recurrent topics in Kaixuan Chen's work include EEG and Brain-Computer Interfaces (7 papers), Anomaly Detection Techniques and Applications (7 papers) and Gaze Tracking and Assistive Technology (6 papers). Kaixuan Chen is often cited by papers focused on EEG and Brain-Computer Interfaces (7 papers), Anomaly Detection Techniques and Applications (7 papers) and Gaze Tracking and Assistive Technology (6 papers). Kaixuan Chen collaborates with scholars based in Australia, China and Denmark. Kaixuan Chen's co-authors include Dalin Zhang, Lina Yao, Xiaojun Chang, Yunhao Liu, Sen Wang, Zhiwen Yu, Xianzhi Wang, Feiping Nie, Bin Guo and Jessica J. M. Monaghan and has published in prestigious journals such as ACM Computing Surveys, IEEE Transactions on Cybernetics and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Kaixuan Chen

19 papers receiving 1.4k citations

Hit Papers

A Semisupervised Recurren... 2019 2026 2021 2023 2019 2019 2021 100 200 300

Author Peers

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

Author Last Decade Papers Cites
Kaixuan Chen 575 464 439 223 201 20 1.4k
Hesam Sagha 1.1k 1.9× 260 0.6× 580 1.3× 410 1.8× 163 0.8× 37 1.7k
Mohamed A. Bencherif 235 0.4× 600 1.3× 393 0.9× 206 0.9× 216 1.1× 32 1.4k
Jingwei Too 246 0.4× 294 0.6× 818 1.9× 378 1.7× 149 0.7× 41 1.7k
Christin Schäfer 617 1.1× 348 0.8× 706 1.6× 94 0.4× 76 0.4× 15 1.5k
Uğur Halıcı 353 0.6× 666 1.4× 248 0.6× 88 0.4× 245 1.2× 69 1.4k
Jyh‐Yeong Chang 290 0.5× 413 0.9× 567 1.3× 132 0.6× 199 1.0× 55 1.4k
Cosimo Ieracitano 146 0.3× 854 1.8× 434 1.0× 133 0.6× 124 0.6× 40 1.7k
Mohammad I. Daoud 254 0.4× 284 0.6× 259 0.6× 262 1.2× 205 1.0× 81 1.3k
Paul von Bünau 226 0.4× 468 1.0× 538 1.2× 84 0.4× 126 0.6× 18 1.3k
Chuang Lin 380 0.7× 728 1.6× 180 0.4× 699 3.1× 165 0.8× 74 1.6k

Countries citing papers authored by Kaixuan Chen

Since Specialization
Citations

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

Fields of papers citing papers by Kaixuan Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kaixuan Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Kaixuan Chen. A scholar is included among the top collaborators of Kaixuan Chen 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 Kaixuan Chen. Kaixuan Chen 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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