Ling Bai

86 total papers · 609 total citations
50 papers, 333 citations indexed

About

Ling Bai is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Environmental Engineering. According to data from OpenAlex, Ling Bai has authored 50 papers receiving a total of 333 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 6 papers in Environmental Engineering. Recurrent topics in Ling Bai's work include Advanced ceramic materials synthesis (5 papers), 3D Surveying and Cultural Heritage (5 papers) and Robotics and Sensor-Based Localization (4 papers). Ling Bai is often cited by papers focused on Advanced ceramic materials synthesis (5 papers), 3D Surveying and Cultural Heritage (5 papers) and Robotics and Sensor-Based Localization (4 papers). Ling Bai collaborates with scholars based in China, Canada and United States. Ling Bai's co-authors include Yinguo Li, Fen Zhao, Zhong Qu, Ling Liu, Zheng Liu, Fangchao Hu, Rakiba Rayhana, Xiaodong Mao, Changchun Ge and Kuo Chen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Renewable and Sustainable Energy Reviews and PLoS ONE.

In The Last Decade

Ling Bai

43 papers receiving 322 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 Bai 68 62 55 47 32 50 333
Shazmin Aniza Abdul Shukor 55 0.8× 19 0.3× 24 0.4× 81 1.7× 13 0.4× 74 350
Yinli Jin 25 0.4× 24 0.4× 17 0.3× 74 1.6× 43 1.3× 44 394
Himanshu Sharma 51 0.8× 14 0.2× 17 0.3× 12 0.3× 28 0.9× 39 314
Yong Zhang 78 1.1× 27 0.4× 6 0.1× 133 2.8× 106 3.3× 51 353
Maofa Wang 38 0.6× 11 0.2× 16 0.3× 52 1.1× 152 4.8× 55 387
Yutaka Kaizu 23 0.3× 10 0.2× 30 0.5× 52 1.1× 7 0.2× 42 361
Juan Botero-Valencia 95 1.4× 20 0.3× 18 0.3× 40 0.9× 29 0.9× 56 367
Himanshu Sharma 17 0.3× 77 1.2× 28 0.5× 53 1.1× 44 1.4× 25 326
Shenghui Yang 62 0.9× 10 0.2× 28 0.5× 22 0.5× 13 0.4× 42 389
Long Yang 25 0.4× 8 0.1× 10 0.2× 128 2.7× 16 0.5× 44 349

Countries citing papers authored by Ling Bai

Since Specialization
Citations

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

Fields of papers citing papers by Ling Bai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ling Bai

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