Kun Su
Impact in
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies
- Infectious Diseases top 0.5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
Papers in
-
- Viral Infections and Vectors 5
- Viral gastroenteritis research and epidemiology 3
-
- Influenza Virus Research Studies 8
- Co-authors
- Ailong Huang (2 shared papers)Bo Wu (2 shared papers)Yong Zhang (2 shared papers)Jingfu Qiu (2 shared papers)Qin Li (2 shared papers)Haijun Deng (1 shared paper)Fan Zhang (1 shared paper)Wei Xü (1 shared paper)
- Journals
- Nature Medicine (2 papers)International Journal of Environmental Research and Public Health (2 papers)International Journal of Infectious Diseases (2 papers)Infectious Disease Modelling (1 paper)Medicine (1 paper)
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Kun Su
26 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 125
- Modeling and Simulation 404
- Infectious Diseases 1.6k
- Neurology 318
- Health 90
- Obstetrics and Gynecology 81
Countries citing papers authored by Kun Su
This map shows the geographic impact of Kun Su'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 Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Su more than expected).
Fields of papers citing papers by Kun Su
This network shows the impact of papers produced by Kun Su. 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 Su. The network helps show where Kun Su may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun Su, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Clinical and immunological assessment of asymptomatic SARS-CoV-2 infections Hit paper breakdown → | 2020 | 1695 |
| 2 | 2020 | 51 | |
| 3 | 2022 | 48 | |
| 4 | 2018 | 43 | |
| 5 | 2020 | 26 | |
| 6 | 2018 | 22 | |
| 7 | 2020 | 20 | |
| 8 | 2017 | 16 | |
| 9 | 2019 | 15 | |
| 10 | 2021 | 11 | |
| 11 | 2022 | 8 | |
| 12 | 2022 | 7 | |
| 13 | 2014 | 7 | |
| 14 | 2018 | 7 | |
| 15 | 2019 | 5 | |
| 16 | 2022 | 4 | |
| 17 | 2022 | 4 | |
| 18 | 2016 | 4 | |
| 19 | 2012 | 4 | |
| 20 | 2016 | 3 |
About Kun Su
Kun Su is a scholar working on Infectious Diseases, Epidemiology, Modeling and Simulation, Agronomy and Crop Science and Computer Networks and Communications, having authored 28 papers that have together received 2.0k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (8 papers), COVID-19 epidemiological studies (7 papers), Animal Disease Management and Epidemiology (5 papers), Viral Infections and Vectors (5 papers), Cognitive Radio Networks and Spectrum Sensing (3 papers), Viral gastroenteritis research and epidemiology (3 papers), Streptococcal Infections and Treatments (3 papers) and Rabies epidemiology and control (3 papers). The work is most often cited by research in Modeling and Simulation (404 citations), Infectious Diseases (1.6k citations), Neurology (318 citations), Health (90 citations) and Obstetrics and Gynecology (81 citations). Kun Su has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Ailong Huang, Bo Wu, Yong Zhang, Jingfu Qiu, Qin Li, Haijun Deng, Fan Zhang, Wei Xü, Jieli Hu and Jun Yuan. Their work appears in journals such as Nature Medicine, International Journal of Environmental Research and Public Health, International Journal of Infectious Diseases, Infectious Disease Modelling and Medicine.
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.