Shen Gao

159 total papers · 1.2k total citations
72 papers, 695 citations indexed

About

Shen Gao is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Shen Gao has authored 72 papers receiving a total of 695 indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Artificial Intelligence, 18 papers in Information Systems and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Shen Gao's work include Topic Modeling (34 papers), Natural Language Processing Techniques (23 papers) and Advanced Text Analysis Techniques (15 papers). Shen Gao is often cited by papers focused on Topic Modeling (34 papers), Natural Language Processing Techniques (23 papers) and Advanced Text Analysis Techniques (15 papers). Shen Gao collaborates with scholars based in China, United States and Saudi Arabia. Shen Gao's co-authors include Rui Yan, Dongyan Zhao, Xiuying Chen, Zhaochun Ren, Chongyang Tao, Zhangming Chan, Mingyue Shang, Wei Wu, Mingzhe Li and Piji Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, Energy Economics and IEEE Transactions on Vehicular Technology.

In The Last Decade

Shen Gao

59 papers receiving 664 citations

Author Peers

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

Author Last Decade Papers Cites
Shen Gao 538 137 125 36 34 72 695
Qika Lin 464 0.9× 135 1.0× 114 0.9× 48 1.3× 27 0.8× 40 686
Hao Wang 449 0.8× 252 1.8× 110 0.9× 13 0.4× 36 1.1× 48 640
Jie Chen 481 0.9× 168 1.2× 77 0.6× 32 0.9× 30 0.9× 81 730
Federico Cerutti 540 1.0× 79 0.6× 57 0.5× 35 1.0× 59 1.7× 69 767
Lixin Cui 348 0.6× 79 0.6× 139 1.1× 36 1.0× 28 0.8× 50 655
Satoshi Oyama 435 0.8× 211 1.5× 117 0.9× 30 0.8× 51 1.5× 83 733
Fuad Rahman 354 0.7× 102 0.7× 360 2.9× 22 0.6× 45 1.3× 84 733
Jipeng Qiang 492 0.9× 126 0.9× 100 0.8× 22 0.6× 27 0.8× 63 716
Ismail Hmeidi 432 0.8× 219 1.6× 94 0.8× 48 1.3× 61 1.8× 45 749
Yu Zhao 482 0.9× 69 0.5× 266 2.1× 24 0.7× 45 1.3× 53 750

Countries citing papers authored by Shen Gao

Since Specialization
Citations

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

Fields of papers citing papers by Shen Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shen Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Shen Gao. A scholar is included among the top collaborators of Shen Gao 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 Shen Gao. Shen Gao 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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2026