Meng Hu

50 total papers · 648 total citations
30 papers, 427 citations indexed

About

Meng Hu is a scholar working on Statistics and Probability, Economics and Econometrics and Artificial Intelligence. According to data from OpenAlex, Meng Hu has authored 30 papers receiving a total of 427 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Statistics and Probability, 8 papers in Economics and Econometrics and 7 papers in Artificial Intelligence. Recurrent topics in Meng Hu's work include Statistical Methods in Clinical Trials (8 papers), Computational Drug Discovery Methods (7 papers) and Neural dynamics and brain function (6 papers). Meng Hu is often cited by papers focused on Statistical Methods in Clinical Trials (8 papers), Computational Drug Discovery Methods (7 papers) and Neural dynamics and brain function (6 papers). Meng Hu collaborates with scholars based in United States, France and China. Meng Hu's co-authors include Hualou Liang, Liang Zhao, Xiajing Gong, Ping Ren, Wu Li, Mahashweta Basu, Yi Zhang, Xiaohui Jiang, Andrew Babiskin and Robert Lionberger and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and SHILAP Revista de lepidopterología.

In The Last Decade

Meng Hu

28 papers receiving 419 citations

Author Peers

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

Author Last Decade Papers Cites
Meng Hu 99 73 73 62 54 30 427
Damien François 26 0.3× 204 2.8× 21 0.3× 37 0.6× 25 0.5× 25 415
Christian Merkwirth 24 0.2× 108 1.5× 141 1.9× 112 1.8× 5 0.1× 24 409
Marcos Gestal 35 0.4× 59 0.8× 91 1.2× 131 2.1× 9 0.2× 40 400
Kevin S. Xu 58 0.6× 142 1.9× 9 0.1× 33 0.5× 31 0.6× 29 470
Evgeny Verbitskiy 25 0.3× 24 0.3× 26 0.4× 19 0.3× 12 0.2× 34 390
Hao Wang 9 0.1× 122 1.7× 23 0.3× 16 0.3× 33 0.6× 37 395
Johannes Rauh 86 0.9× 114 1.6× 129 1.8× 29 0.5× 9 0.2× 31 390
Raymond Bonner 24 0.2× 110 1.5× 28 0.4× 14 0.2× 8 0.1× 17 488
Hui Xiong 24 0.2× 32 0.4× 6 0.1× 47 0.8× 53 1.0× 36 390
Earl E. Gose 12 0.1× 183 2.5× 27 0.4× 29 0.5× 14 0.3× 24 456

Countries citing papers authored by Meng Hu

Since Specialization
Citations

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

Fields of papers citing papers by Meng Hu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Meng Hu

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