Hangyu Mao

80 total papers · 658 total citations
25 papers, 228 citations indexed

About

Hangyu Mao is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, Hangyu Mao has authored 25 papers receiving a total of 228 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 6 papers in Electrical and Electronic Engineering and 5 papers in Computer Networks and Communications. Recurrent topics in Hangyu Mao's work include Reinforcement Learning in Robotics (11 papers), Artificial Intelligence in Games (2 papers) and Digital Transformation in Industry (2 papers). Hangyu Mao is often cited by papers focused on Reinforcement Learning in Robotics (11 papers), Artificial Intelligence in Games (2 papers) and Digital Transformation in Industry (2 papers). Hangyu Mao collaborates with scholars based in China, Sweden and United Kingdom. Hangyu Mao's co-authors include Zhen Xiao, Ni Yan, Bin He, Jianye Hao, Wulong Liu, Jun Luo, Jun Wang, Zhengchao Zhang, Dong Li and Yu Liu and has published in prestigious journals such as IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Cybernetics and Neurocomputing.

In The Last Decade

Hangyu Mao

22 papers receiving 220 citations

Author Peers

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

Author Last Decade Papers Cites
Hangyu Mao 124 62 34 27 25 25 228
Roxana Rădulescu 112 0.9× 48 0.8× 40 1.2× 48 1.8× 31 1.2× 25 322
Abdulaziz Aldaej 72 0.6× 73 1.2× 22 0.6× 24 0.9× 13 0.5× 26 198
Landon Kraemer 167 1.3× 63 1.0× 69 2.0× 31 1.1× 11 0.4× 17 300
Hongyao Tang 107 0.9× 33 0.5× 47 1.4× 35 1.3× 12 0.5× 18 201
Marcela Quiróz-Castellanos 62 0.5× 65 1.0× 24 0.7× 42 1.6× 82 3.3× 21 258
Jilles Dibangoye 124 1.0× 50 0.8× 48 1.4× 29 1.1× 19 0.8× 22 244
Johan Källström 81 0.7× 29 0.5× 17 0.5× 23 0.9× 20 0.8× 11 206
Yali Wu 66 0.5× 26 0.4× 29 0.9× 29 1.1× 21 0.8× 25 165
Lan Yang 53 0.4× 67 1.1× 17 0.5× 12 0.4× 19 0.8× 19 313
Peter Sunehag 218 1.8× 86 1.4× 37 1.1× 35 1.3× 11 0.4× 26 332

Countries citing papers authored by Hangyu Mao

Since Specialization
Citations

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

Fields of papers citing papers by Hangyu Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hangyu Mao

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