Baoyu Jing

42 total papers · 622 total citations
18 papers, 269 citations indexed

About

Baoyu Jing is a scholar working on Artificial Intelligence, Information Systems and Signal Processing. According to data from OpenAlex, Baoyu Jing has authored 18 papers receiving a total of 269 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 3 papers in Information Systems and 3 papers in Signal Processing. Recurrent topics in Baoyu Jing's work include Advanced Graph Neural Networks (7 papers), Topic Modeling (7 papers) and Text and Document Classification Technologies (3 papers). Baoyu Jing is often cited by papers focused on Advanced Graph Neural Networks (7 papers), Topic Modeling (7 papers) and Text and Document Classification Technologies (3 papers). Baoyu Jing collaborates with scholars based in United States, China and Switzerland. Baoyu Jing's co-authors include Hanghang Tong, Zeya Wang, Yuchen Yan, Yada Zhu, Deqing Wang, Lihui Liu, Hongyi Xin, Tao Yang, Wei Fan and Fuzhen Zhuang and has published in prestigious journals such as IEEE Transactions on Cybernetics, IEEE Transactions on Neural Networks and Learning Systems and Neural Networks.

In The Last Decade

Baoyu Jing

15 papers receiving 263 citations

Author Peers

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

Author Last Decade Papers Cites
Baoyu Jing 221 39 33 31 30 18 269
Chaoqi Yang 148 0.7× 23 0.6× 31 0.9× 9 0.3× 30 1.0× 24 234
Ian En-Hsu Yen 277 1.3× 60 1.5× 24 0.7× 4 0.1× 92 3.1× 23 325
Giannis Nikolentzos 209 0.9× 23 0.6× 96 2.9× 7 0.2× 68 2.3× 17 272
Christopher L. Carmichael 91 0.4× 110 2.8× 30 0.9× 19 0.6× 48 1.6× 11 206
Mostofa Patwary 146 0.7× 26 0.7× 16 0.5× 8 0.3× 39 1.3× 10 207
Wenxiong Liao 186 0.8× 28 0.7× 5 0.2× 16 0.5× 25 0.8× 16 257
Xuan Bi 60 0.3× 23 0.6× 8 0.2× 43 1.4× 21 0.7× 27 232
Cedric De Boom 136 0.6× 38 1.0× 19 0.6× 4 0.1× 38 1.3× 19 226
Sahar Vahdati 149 0.7× 33 0.8× 18 0.5× 8 0.3× 34 1.1× 28 219
Wang Gao 203 0.9× 95 2.4× 43 1.3× 5 0.2× 24 0.8× 29 301

Countries citing papers authored by Baoyu Jing

Since Specialization
Citations

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

Fields of papers citing papers by Baoyu Jing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Baoyu Jing

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