Kun Wu
Impact in
- Neurology top 5%
- Transcranial Magnetic Stimulation Studies
- Cognitive Neuroscience top 5%
- Functional Brain Connectivity Studies
Papers in
-
- Neural dynamics and brain function 9
- Memory and Neural Mechanisms 5
- EEG and Brain-Computer Interfaces 4
- Co-authors
- L. Stan Leung (7 shared papers)Xiao‐Guang Chen (12 shared papers)Keith A. Hawkins (3 shared papers)Jinbao Gu (6 shared papers)Jiabao Xu (4 shared papers)Xinghua Su (4 shared papers)Guofa Zhou (4 shared papers)Guiyun Yan (5 shared papers)
- Journals
- Parasites & Vectors (5 papers)Neuroscience (3 papers)Cerebral Cortex (3 papers)Insect Science (2 papers)Hippocampus (2 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Kun Wu
59 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 124
- Neurology 142
- Cognitive Neuroscience 326
- Insect Science 201
- Cellular and Molecular Neuroscience 238
- Public Health, Environmental and Occupational Health 314
Countries citing papers authored by Kun Wu
This map shows the geographic impact of Kun 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 Kun Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Wu more than expected).
Fields of papers citing papers by Kun Wu
This network shows the impact of papers produced by Kun 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 Kun Wu. The network helps show where Kun Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 119 | |
| 2 | 2017 | 83 | |
| 3 | 2018 | 75 | |
| 4 | 2018 | 70 | |
| 5 | 2009 | 65 | |
| 6 | 2013 | 62 | |
| 7 | 2019 | 51 | |
| 8 | 2003 | 43 | |
| 9 | 2001 | 41 | |
| 10 | 2013 | 34 | |
| 11 | 2009 | 32 | |
| 12 | 2021 | 28 | |
| 13 | 1998 | 28 | |
| 14 | 2022 | 27 | |
| 15 | 2018 | 24 | |
| 16 | 1998 | 23 | |
| 17 | 2019 | 23 | |
| 18 | 2019 | 21 | |
| 19 | 2020 | 19 | |
| 20 | 2004 | 17 |
About Kun Wu
Kun Wu is a scholar working on Molecular Biology, Cognitive Neuroscience, Cellular and Molecular Neuroscience, Public Health, Environmental and Occupational Health and Organic Chemistry, having authored 66 papers that have together received 1.1k indexed citations. Recurring topics across this work include Mosquito-borne diseases and control (10 papers), Neuroscience and Neuropharmacology Research (9 papers), Neural dynamics and brain function (9 papers), Antimicrobial agents and applications (5 papers), Memory and Neural Mechanisms (5 papers), Malaria Research and Control (5 papers), EEG and Brain-Computer Interfaces (4 papers) and Dengue and Mosquito Control Research (4 papers). The work is most often cited by research in Neurology (142 citations), Cognitive Neuroscience (326 citations), Insect Science (201 citations), Cellular and Molecular Neuroscience (238 citations) and Public Health, Environmental and Occupational Health (314 citations). Kun Wu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include L. Stan Leung, Xiao‐Guang Chen, Keith A. Hawkins, Jinbao Gu, Jiabao Xu, Xinghua Su, Guofa Zhou, Guiyun Yan, Daibin Zhong and Yang Wu. Their work appears in journals such as Parasites & Vectors, Neuroscience, Cerebral Cortex, Insect Science and Hippocampus.
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.