Ling Gao

43 total papers · 450 total citations
29 papers, 293 citations indexed

About

Ling Gao is a scholar working on Atmospheric Science, Global and Planetary Change and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ling Gao has authored 29 papers receiving a total of 293 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Atmospheric Science, 7 papers in Global and Planetary Change and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ling Gao's work include Atmospheric chemistry and aerosols (7 papers), Atmospheric and Environmental Gas Dynamics (6 papers) and Atmospheric Ozone and Climate (6 papers). Ling Gao is often cited by papers focused on Atmospheric chemistry and aerosols (7 papers), Atmospheric and Environmental Gas Dynamics (6 papers) and Atmospheric Ozone and Climate (6 papers). Ling Gao collaborates with scholars based in China, Thailand and Saudi Arabia. Ling Gao's co-authors include Nan Sheng, Ping Xuan, Tiangang Zhang, Toshiya Nakaguchi, Hanchao Jiang, Zhongli Ding, Zihua Tang, Junliang Ji, Lan Huang and Yan Wang and has published in prestigious journals such as Scientific Reports, Atmospheric Environment and Expert Systems with Applications.

In The Last Decade

Ling Gao

29 papers receiving 281 citations

Author Peers

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

Author Last Decade Papers Cites
Ling Gao 96 82 65 48 41 29 293
Ziqian Li 38 0.4× 91 1.1× 33 0.5× 52 1.1× 19 0.5× 33 366
Daniela De Canditiis 45 0.5× 105 1.3× 39 0.6× 32 0.7× 12 0.3× 37 316
A. Srinivasan 22 0.2× 68 0.8× 15 0.2× 63 1.3× 35 0.9× 22 342
Zhixiang Wu 33 0.3× 113 1.4× 8 0.1× 44 0.9× 39 1.0× 34 319
Radu Herbei 36 0.4× 28 0.3× 35 0.5× 143 3.0× 2 0.0× 24 325
Bo Cui 114 1.2× 35 0.4× 88 1.4× 43 0.9× 4 0.1× 34 291
Tianyu Zhang 69 0.7× 25 0.3× 26 0.4× 41 0.9× 3 0.1× 31 305
Ali Muhamed Ali 16 0.2× 65 0.8× 27 0.4× 68 1.4× 41 1.0× 21 298
Yeping Zhang 53 0.6× 31 0.4× 47 0.7× 49 1.0× 15 0.4× 52 236
Bo Long 72 0.8× 22 0.3× 18 0.3× 76 1.6× 30 327

Countries citing papers authored by Ling Gao

Since Specialization
Citations

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

Fields of papers citing papers by Ling Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ling Gao

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