Sumeng Li
Impact in
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Viral Infections and Vectors
-
- COVID-19 epidemiological studies
Papers in
-
- COVID-19 Clinical Research Studies 8
- SARS-CoV-2 and COVID-19 Research 6
-
- Long-Term Effects of COVID-19 4
- Co-authors
- Sihong Lu (9 shared papers)Dongliang Yang (9 shared papers)Mengji Lu (4 shared papers)Huadong Li (4 shared papers)Xin Zheng (8 shared papers)Boyun Liang (8 shared papers)Hua Wang (5 shared papers)Jia Liu (5 shared papers)
- Journals
- Frontiers in Immunology (5 papers)Immunology (1 paper)Hepatology Research (1 paper)The Journal of Trauma: Injury, Infection, and Critical Care (1 paper)Cells (1 paper)
- Partner nations
- ChinaGermanySouth Sudan
In The Last Decade
Sumeng Li
16 papers receiving 223 citations
Peers
Comparison fields: 5 of 59
- Infectious Diseases 141
- Modeling and Simulation 12
- Neurology 28
- Oncology 23
- Animal Science and Zoology 9
Countries citing papers authored by Sumeng Li
This map shows the geographic impact of Sumeng Li'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 Sumeng Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumeng Li more than expected).
Fields of papers citing papers by Sumeng Li
This network shows the impact of papers produced by Sumeng Li. 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 Sumeng Li. The network helps show where Sumeng Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Sumeng Li, 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 | 2021 | 54 | |
| 2 | 2020 | 44 | |
| 3 | 2021 | 42 | |
| 4 | 2020 | 21 | |
| 5 | 2020 | 17 | |
| 6 | 2021 | 12 | |
| 7 | 2022 | 12 | |
| 8 | 2021 | 7 | |
| 9 | 2020 | 5 | |
| 10 | 2025 | 4 | |
| 11 | 2021 | 3 | |
| 12 | 2025 | 2 | |
| 13 | 2025 | 2 | |
| 14 | 2024 | 2 | |
| 15 | 2022 | 1 | |
| 16 | 2020 | 1 | |
| 17 | 2025 | 0 |
About Sumeng Li
Sumeng Li is a scholar working on Infectious Diseases, Neurology, Oncology, Epidemiology and Modeling and Simulation, having authored 17 papers that have together received 229 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (8 papers), SARS-CoV-2 and COVID-19 Research (6 papers), Long-Term Effects of COVID-19 (4 papers), COVID-19 epidemiological studies (2 papers), Vitamin C and Antioxidants Research (1 paper), Inflammatory Biomarkers in Disease Prognosis (1 paper), Radiomics and Machine Learning in Medical Imaging (1 paper) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Infectious Diseases (141 citations), Modeling and Simulation (12 citations), Neurology (28 citations), Oncology (23 citations) and Animal Science and Zoology (9 citations). Sumeng Li has collaborated with scholars based in China, Germany and South Sudan. Frequent co-authors include Sihong Lu, Dongliang Yang, Mengji Lu, Huadong Li, Xin Zheng, Boyun Liang, Hua Wang, Jia Liu, Ulf Dittmer and Xin Zheng. Their work appears in journals such as Frontiers in Immunology, Immunology, Hepatology Research, The Journal of Trauma: Injury, Infection, and Critical Care and Cells.
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.