Mufei Li
Impact in
- Otorhinolaryngology top 5%
- Head and Neck Cancer Studies
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- Sports Performance and Training
Papers in
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- Tuberculosis Research and Epidemiology 9
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- Advanced Graph Neural Networks 5
- Co-authors
- Lei Gao (17 shared papers)Yu Yang (10 shared papers)Cong Gao (3 shared papers)Xiangwei Li (15 shared papers)Qi Jin (12 shared papers)Xiangwei Li (2 shared papers)Feng Zhou (1 shared paper)Fang Ma (1 shared paper)
- Journals
- Scientific Reports (5 papers)PLoS ONE (4 papers)Journal of Infection (3 papers)Frontiers of Medicine (2 papers)Chemosphere (2 papers)
- Partner nations
- ChinaUnited StatesSwitzerland
In The Last Decade
Mufei Li
36 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 140
- Otorhinolaryngology 74
- Orthopedics and Sports Medicine 118
- Infectious Diseases 153
- Genetics 212
- Health, Toxicology and Mutagenesis 93
Countries citing papers authored by Mufei Li
This map shows the geographic impact of Mufei 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 Mufei Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mufei Li more than expected).
Fields of papers citing papers by Mufei Li
This network shows the impact of papers produced by Mufei 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 Mufei Li. The network helps show where Mufei Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Mufei 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
Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs | 2019 | 273 |
| 2 | 2013 | 216 | |
| 3 | 2012 | 122 | |
| 4 | 2020 | 48 | |
| 5 | 2016 | 45 | |
| 6 | 2017 | 32 | |
| 7 | 2017 | 32 | |
| 8 | 2019 | 29 | |
| 9 | 2013 | 29 | |
| 10 | 2012 | 25 | |
| 11 | 2021 | 25 | |
| 12 | 2019 | 25 | |
| 13 | 2017 | 23 | |
| 14 | 2013 | 22 | |
| 15 | 2019 | 22 | |
| 16 | 2016 | 19 | |
| 17 | 2022 | 18 | |
| 18 | 2021 | 17 | |
| 19 | 2021 | 16 | |
| 20 | 2015 | 16 |
About Mufei Li
Mufei Li is a scholar working on Infectious Diseases, Artificial Intelligence, Analytical Chemistry, Health, Toxicology and Mutagenesis and Epidemiology, having authored 37 papers that have together received 1.2k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (9 papers), Analytical chemistry methods development (6 papers), Advanced Graph Neural Networks (5 papers), Toxic Organic Pollutants Impact (5 papers), Cervical Cancer and HPV Research (4 papers), Computational Drug Discovery Methods (4 papers), Machine Learning in Materials Science (3 papers) and Immune responses and vaccinations (2 papers). The work is most often cited by research in Otorhinolaryngology (74 citations), Orthopedics and Sports Medicine (118 citations), Infectious Diseases (153 citations), Genetics (212 citations) and Health, Toxicology and Mutagenesis (93 citations). Mufei Li has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Lei Gao, Yu Yang, Cong Gao, Xiangwei Li, Qi Jin, Xiangwei Li, Feng Zhou, Fang Ma, Feng Zhou and Henan Xin. Their work appears in journals such as Scientific Reports, PLoS ONE, Journal of Infection, Frontiers of Medicine and Chemosphere.
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.