Kevin Hu

54 total papers · 866 total citations
6 papers, 174 citations indexed

About

Kevin Hu is a scholar working on Artificial Intelligence, Communication and Computer Networks and Communications. According to data from OpenAlex, Kevin Hu has authored 6 papers receiving a total of 174 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 2 papers in Communication and 1 paper in Computer Networks and Communications. Recurrent topics in Kevin Hu's work include Natural Language Processing Techniques (3 papers), Topic Modeling (3 papers) and Wikis in Education and Collaboration (2 papers). Kevin Hu is often cited by papers focused on Natural Language Processing Techniques (3 papers), Topic Modeling (3 papers) and Wikis in Education and Collaboration (2 papers). Kevin Hu collaborates with scholars based in United States, France and Spain. Kevin Hu's co-authors include César A. Hidalgo, Bruno Gonçalves, Alessandro Vespignani, Steven Pinker, Amy Yu, Wenfeng Xia, James R. Driscoll, Haiyong Xie, Diego López and Sharon L. Abbott and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Scientific Data and Text REtrieval Conference.

In The Last Decade

Kevin Hu

5 papers receiving 164 citations

Author Peers

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

Author Last Decade Papers Cites
Kevin Hu 42 35 34 34 33 6 174
Ronald T. Wohlstein 14 0.3× 29 0.8× 134 3.9× 40 1.2× 27 0.8× 7 261
Despoina Antonakaki 32 0.8× 37 1.1× 99 2.9× 19 0.6× 142 4.3× 13 292
Drew Conway 51 1.2× 11 0.3× 74 2.2× 10 0.3× 92 2.8× 7 249
David M. Beskow 30 0.7× 34 1.0× 128 3.8× 10 0.3× 61 1.8× 11 212
Mirko Lai 53 1.3× 45 1.3× 65 1.9× 8 0.2× 138 4.2× 17 231
Weicong Ding 70 1.7× 29 0.8× 94 2.8× 20 0.6× 82 2.5× 13 263
Martijn Spitters 57 1.4× 22 0.6× 106 3.1× 21 0.6× 122 3.7× 15 285
Muhammad Ali 40 1.0× 9 0.3× 119 3.5× 7 0.2× 98 3.0× 10 249
John Ternovski 73 1.7× 15 0.4× 102 3.0× 5 0.1× 25 0.8× 9 186
Giulia Bonelli 26 0.6× 103 2.9× 104 3.1× 12 0.4× 26 0.8× 3 255

Countries citing papers authored by Kevin Hu

Since Specialization
Citations

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

Fields of papers citing papers by Kevin Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kevin Hu

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