Chengyuan Wu

206 total papers · 3.9k total citations
125 papers, 2.1k citations indexed

About

Chengyuan Wu is a scholar working on Neurology, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Chengyuan Wu has authored 125 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Neurology, 38 papers in Cognitive Neuroscience and 37 papers in Cellular and Molecular Neuroscience. Recurrent topics in Chengyuan Wu's work include Neurological disorders and treatments (43 papers), Epilepsy research and treatment (31 papers) and EEG and Brain-Computer Interfaces (21 papers). Chengyuan Wu is often cited by papers focused on Neurological disorders and treatments (43 papers), Epilepsy research and treatment (31 papers) and EEG and Brain-Computer Interfaces (21 papers). Chengyuan Wu collaborates with scholars based in United States, China and United Kingdom. Chengyuan Wu's co-authors include Ashwini Sharan, Michael R. Sperling, Andrew Campbell, James J. Evans, Christopher Skidmore, Yuguang Liu, Caio M. Matias, Joseph I. Tracy, Joon Y. Kang and Maromi Nei and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Nature Neuroscience.

In The Last Decade

Chengyuan Wu

121 papers receiving 2.1k citations

Author Peers

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

Author Last Decade Papers Cites
Chengyuan Wu 831 782 776 751 276 125 2.1k
Romain Carron 920 1.1× 953 1.2× 1.3k 1.6× 905 1.2× 262 0.9× 100 2.5k
Shigeki Kameyama 720 0.9× 984 1.3× 731 0.9× 742 1.0× 266 1.0× 112 2.6k
Carlo Efisio Marras 1.1k 1.4× 658 0.8× 469 0.6× 662 0.9× 439 1.6× 127 3.2k
Didier Scavarda 723 0.9× 1.1k 1.5× 899 1.2× 764 1.0× 212 0.8× 112 2.7k
Juan Álvarez‐Linera 646 0.8× 529 0.7× 864 1.1× 399 0.5× 748 2.7× 90 2.6k
Taylor J. Abel 521 0.6× 631 0.8× 604 0.8× 411 0.5× 113 0.4× 109 1.7k
Joseph R. Smith 522 0.6× 1.4k 1.7× 1.4k 1.8× 882 1.2× 276 1.0× 101 2.7k
Freimut D. Juengling 828 1.0× 433 0.6× 596 0.8× 578 0.8× 401 1.5× 76 2.6k
A. Earl Walker 764 0.9× 396 0.5× 418 0.5× 454 0.6× 125 0.5× 103 2.0k
Hatice Tankişi 1.3k 1.5× 471 0.6× 529 0.7× 501 0.7× 364 1.3× 154 2.8k

Countries citing papers authored by Chengyuan Wu

Since Specialization
Citations

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

Fields of papers citing papers by Chengyuan Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chengyuan Wu

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