Kun Gai

49 papers and 1.8k indexed citations i.

About

Kun Gai is a scholar working on Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Kun Gai has authored 49 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Information Systems, 24 papers in Artificial Intelligence and 23 papers in Computer Vision and Pattern Recognition. Recurrent topics in Kun Gai’s work include Recommender Systems and Techniques (28 papers), Advanced Bandit Algorithms Research (13 papers) and Advanced Graph Neural Networks (7 papers). Kun Gai is often cited by papers focused on Recommender Systems and Techniques (28 papers), Advanced Bandit Algorithms Research (13 papers) and Advanced Graph Neural Networks (7 papers). Kun Gai collaborates with scholars based in China, United States and Hong Kong. Kun Gai's co-authors include Guorui Zhou, Ying Fan, Xiaoqiang Zhu, Zhu Han, Han Li, Junqi Jin, Xiao Ma, Weijie Bian, Chang Zhou and Na Mou and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Neurocomputing and 2009 IEEE Conference on Computer Vision and Pattern Recognition.

In The Last Decade

Co-authorship network of co-authors of Kun Gai i

Fields of papers citing papers by Kun Gai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Kun Gai

Since Specialization
Citations

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

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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