Fei Kuang
Impact in
- Immunology top 10%
- T-cell and B-cell Immunology
- Immune Cell Function and Interaction
- Rheumatology top 10%
- Eosinophilic Disorders and Syndromes
Papers in
-
- T-cell and B-cell Immunology 4
- Immune Cell Function and Interaction 4
- Co-authors
- Matthew D. Scharff (4 shared papers)Jonathan U. Peled (3 shared papers)Sergio Roa (2 shared papers)Maria D. Iglesias-Ussel (2 shared papers)Susan L. Kalis (1 shared paper)Myron F. Goodman (1 shared paper)Amy D. Klion (5 shared papers)Zhonghui Luo (2 shared papers)
- Journals
- Journal of Allergy and Clinical Immunology (3 papers)Proceedings of the National Academy of Sciences (2 papers)The Journal of Allergy and Clinical Immunology In Practice (2 papers)Frontiers in Oncology (2 papers)Journal of Materials Chemistry B (2 papers)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Fei Kuang
29 papers receiving 833 citations
Peers
Comparison fields: 5 of 92
- Immunology 313
- Rheumatology 86
- Virology 23
- Molecular Biology 324
- Cancer Research 60
Countries citing papers authored by Fei Kuang
This map shows the geographic impact of Fei Kuang'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 Fei Kuang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fei Kuang more than expected).
Fields of papers citing papers by Fei Kuang
This network shows the impact of papers produced by Fei Kuang. 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 Fei Kuang. The network helps show where Fei Kuang may publish in the future.
Co-authors
The 25 scholars most cited alongside Fei Kuang, 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 337 | |
| 2 | 2008 | 94 | |
| 3 | 2018 | 60 | |
| 4 | 2023 | 60 | |
| 5 | 2009 | 47 | |
| 6 | 2018 | 44 | |
| 7 | 2017 | 33 | |
| 8 | 2011 | 28 | |
| 9 | 2024 | 23 | |
| 10 | 2022 | 19 | |
| 11 | 2022 | 17 | |
| 12 | 2022 | 14 | |
| 13 | 2019 | 12 | |
| 14 | 2018 | 12 | |
| 15 | 2023 | 11 | |
| 16 | 2012 | 7 | |
| 17 | 2023 | 6 | |
| 18 | 2021 | 5 | |
| 19 | 2007 | 4 | |
| 20 | 2024 | 4 |
About Fei Kuang
Fei Kuang is a scholar working on Immunology, Molecular Biology, Rheumatology, Surgery and Oncology, having authored 31 papers that have together received 850 indexed citations. Recurring topics across this work include T-cell and B-cell Immunology (4 papers), Immune Cell Function and Interaction (4 papers), Eosinophilic Disorders and Syndromes (4 papers), Eosinophilic Esophagitis (3 papers), MXene and MAX Phase Materials (3 papers), Advanced Photocatalysis Techniques (2 papers), Cancer Immunotherapy and Biomarkers (2 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). The work is most often cited by research in Immunology (313 citations), Rheumatology (86 citations), Virology (23 citations), Molecular Biology (324 citations) and Cancer Research (60 citations). Fei Kuang has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Matthew D. Scharff, Jonathan U. Peled, Sergio Roa, Maria D. Iglesias-Ussel, Susan L. Kalis, Myron F. Goodman, Amy D. Klion, Zhonghui Luo, De Luo and Song Su. Their work appears in journals such as Journal of Allergy and Clinical Immunology, Proceedings of the National Academy of Sciences, The Journal of Allergy and Clinical Immunology In Practice, Frontiers in Oncology and Journal of Materials Chemistry B.
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.