Gaowei Yan

117 total papers · 812 total citations
71 papers, 555 citations indexed

About

Gaowei Yan is a scholar working on Control and Systems Engineering, Artificial Intelligence and Mechanical Engineering. According to data from OpenAlex, Gaowei Yan has authored 71 papers receiving a total of 555 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Control and Systems Engineering, 25 papers in Artificial Intelligence and 17 papers in Mechanical Engineering. Recurrent topics in Gaowei Yan's work include Fault Detection and Control Systems (18 papers), Mineral Processing and Grinding (12 papers) and Machine Learning and ELM (11 papers). Gaowei Yan is often cited by papers focused on Fault Detection and Control Systems (18 papers), Mineral Processing and Grinding (12 papers) and Machine Learning and ELM (11 papers). Gaowei Yan collaborates with scholars based in China, Netherlands and United States. Gaowei Yan's co-authors include Tiezhu Qiao, Yusong Pang, Mifeng Ren, Lan Cheng, Gang Xie, Lulu Chen, Changyun Miao, Xinying Xu, Wei Jie and Fuchun Sun and has published in prestigious journals such as IEEE Transactions on Signal Processing, IEEE Access and Energy.

In The Last Decade

Gaowei Yan

61 papers receiving 530 citations

Author Peers

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

Author Last Decade Papers Cites
Gaowei Yan 187 161 146 124 74 71 555
Adam� Zielonka 122 0.7× 95 0.6× 134 0.9× 104 0.8× 57 0.8× 61 580
Quanli Liu 117 0.6× 158 1.0× 217 1.5× 161 1.3× 67 0.9× 75 686
Tamás Bécsi 94 0.5× 287 1.8× 79 0.5× 150 1.2× 107 1.4× 92 638
Hexuan Hu 91 0.5× 171 1.1× 53 0.4× 136 1.1× 56 0.8× 44 520
Xiaochen Hao 137 0.7× 190 1.2× 156 1.1× 110 0.9× 32 0.4× 94 683
Xiaodan Liang 156 0.8× 112 0.7× 211 1.4× 82 0.7× 64 0.9× 49 560
Jian Zheng 63 0.3× 107 0.7× 241 1.7× 94 0.8× 125 1.7× 57 691
Hengrui Ma 124 0.7× 149 0.9× 381 2.6× 120 1.0× 89 1.2× 65 698
Jianchun Xing 67 0.4× 182 1.1× 195 1.3× 101 0.8× 87 1.2× 76 669
Szilárd Aradi 82 0.4× 247 1.5× 67 0.5× 112 0.9× 100 1.4× 78 547

Countries citing papers authored by Gaowei Yan

Since Specialization
Citations

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

Fields of papers citing papers by Gaowei Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gaowei Yan

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