Guojun Mao

73 total papers · 607 total citations
42 papers, 392 citations indexed

About

Guojun Mao is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Guojun Mao has authored 42 papers receiving a total of 392 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 9 papers in Information Systems. Recurrent topics in Guojun Mao's work include Advanced Neural Network Applications (7 papers), Semantic Web and Ontologies (7 papers) and Anomaly Detection Techniques and Applications (5 papers). Guojun Mao is often cited by papers focused on Advanced Neural Network Applications (7 papers), Semantic Web and Ontologies (7 papers) and Anomaly Detection Techniques and Applications (5 papers). Guojun Mao collaborates with scholars based in China, United States and Germany. Guojun Mao's co-authors include Zhenyu Meng, Yan Liang, Xingsi Xue, Hai Zhu, Chao Jiang, Xindong Wu, Chunnian Liu, Xingquan Zhu, Gong Chen and Yong Xu and has published in prestigious journals such as Chemical Engineering Journal, Sensors and Information Sciences.

In The Last Decade

Guojun Mao

37 papers receiving 382 citations

Author Peers

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

Author Last Decade Papers Cites
Guojun Mao 186 77 77 67 57 42 392
Zhen Liu 183 1.0× 163 2.1× 34 0.4× 46 0.7× 94 1.6× 47 444
Nadjet Kamel 232 1.2× 81 1.1× 30 0.4× 65 1.0× 38 0.7× 27 361
Jie Wang 222 1.2× 25 0.3× 119 1.5× 33 0.5× 76 1.3× 38 429
Mohammad Shafiul Alam 194 1.0× 30 0.4× 44 0.6× 42 0.6× 29 0.5× 44 402
Yanpeng Qu 247 1.3× 71 0.9× 19 0.2× 68 1.0× 109 1.9× 49 383
Moonis Ali 150 0.8× 61 0.8× 31 0.4× 34 0.5× 43 0.8× 55 377
Doina Bucur 121 0.7× 52 0.7× 51 0.7× 26 0.4× 30 0.5× 35 433
Mohamed Slimane 212 1.1× 28 0.4× 34 0.4× 72 1.1× 93 1.6× 41 419
Osama Dorgham 168 0.9× 39 0.5× 61 0.8× 19 0.3× 148 2.6× 34 426
Shih-Pang Tseng 130 0.7× 73 0.9× 18 0.2× 53 0.8× 60 1.1× 74 359

Countries citing papers authored by Guojun Mao

Since Specialization
Citations

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

Fields of papers citing papers by Guojun Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guojun Mao

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