Kun Huang
- Immunology top 5%
- interferon and immune responses 9
- Immune Cell Function and Interaction 6
- T-cell and B-cell Immunology 6
- Infectious Diseases top 5%
- COVID-19 Clinical Research Studies 9
- SARS-CoV-2 and COVID-19 Research 8
- Viral gastroenteritis research and epidemiology 6
- Animal Science and Zoology top 2%
- Animal Virus Infections Studies 6
- Immunology and Allergy top 5%
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- Influenza Virus Research Studies 10
- Co-authors
- Elizabeth W. ShoresPaul E. LoveRaymond A. DaynesMeilin JinBarbara A. AraneoDonald J. DudleyZhong ZouHuanchun Chen
- Journals
- Science (1 paper)Proceedings of the National Academy of Sciences (1 paper)Journal of Clinical Investigation (1 paper)
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Kun Huang
65 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 137
- Immunology 824
- Infectious Diseases 553
- Animal Science and Zoology 258
- Immunology and Allergy 108
- Oncology 228
Countries citing papers authored by Kun Huang
This map shows the geographic impact of Kun Huang'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 Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Huang more than expected).
Fields of papers citing papers by Kun Huang
This network shows the impact of papers produced by Kun Huang. 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 Huang. The network helps show where Kun Huang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kun Huang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 8 | |
| 5 | 2023 | 3 | |
| 6 | 2022 | 4 | |
| 7 | 2022 | 10 | |
| 8 | 2022 | 3 | |
| 9 | 2022 | 64 | |
| 10 | 2022 | 1 | |
| 11 | 2021 | 42 | |
| 12 | 2021 | 28 | |
| 13 | 2020 | 213 | |
| 14 | 2020 | 17 | |
| 15 | 2019 | 30 | |
| 16 | Comparative Study Between Chinese and Western Culture in Kung Fu Panda 2 | 2013 | 0 |
| 17 | 2001 | 228 | |
| 18 | 1996 | 19 | |
| 19 | 1994 | 21 | |
| 20 | 1992 | 5 |
About Kun Huang
Kun Huang is a scholar working on Immunology, Infectious Diseases and Animal Science and Zoology, having authored 70 papers that have together received 2.1k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (10 papers), interferon and immune responses (9 papers), COVID-19 Clinical Research Studies (9 papers), SARS-CoV-2 and COVID-19 Research (8 papers), Animal Virus Infections Studies (6 papers), Viral gastroenteritis research and epidemiology (6 papers), Immune Cell Function and Interaction (6 papers) and T-cell and B-cell Immunology (6 papers). The work is most often cited by research in Immunology (824 citations), Infectious Diseases (553 citations) and Animal Science and Zoology (258 citations). Kun Huang has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Elizabeth W. Shores, Paul E. Love, Raymond A. Daynes, Meilin Jin, Barbara A. Araneo, Donald J. Dudley, Zhong Zou, Huanchun Chen, Connie L. Sommers and Rebecca P. Emmons. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Journal of Clinical Investigation.
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.