Lele Ai
Impact in
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
- Viral Infections and Vectors
- COVID-19 Clinical Research Studies
- Viral gastroenteritis research and epidemiology
- Viral Infections and Outbreaks Research
- Animal Science and Zoology top 5%
- Animal Virus Infections Studies
Papers in
-
- Viral Infections and Vectors 15
- Viral Infections and Outbreaks Research 4
-
- Vector-borne infectious diseases 7
- Co-authors
- Changqiang Zhu (24 shared papers)Weilong Tan (24 shared papers)Dan Hu (4 shared papers)Fuqiang Ye (6 shared papers)Changjun Wang (4 shared papers)Lu Yang (4 shared papers)Youjun Feng (2 shared papers)Chenxi Ding (4 shared papers)
- Journals
- Scientific Reports (4 papers)Frontiers in Cellular and Infection Microbiology (3 papers)BMC Public Health (2 papers)Frontiers in Public Health (2 papers)Virus Research (1 paper)
- Partner nations
- ChinaUnited StatesRussia
In The Last Decade
Lele Ai
25 papers receiving 459 citations
Peers
Comparison fields: 5 of 79
- Infectious Diseases 330
- Animal Science and Zoology 94
- Parasitology 57
- Modeling and Simulation 34
- Virology 12
Countries citing papers authored by Lele Ai
This map shows the geographic impact of Lele Ai'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 Lele Ai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lele Ai more than expected).
Fields of papers citing papers by Lele Ai
This network shows the impact of papers produced by Lele Ai. 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 Lele Ai. The network helps show where Lele Ai may publish in the future.
Co-authors
The 25 scholars most cited alongside Lele Ai, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 192 | |
| 2 | 2017 | 48 | |
| 3 | 2021 | 26 | |
| 4 | 2023 | 25 | |
| 5 | 2022 | 22 | |
| 6 | 2020 | 17 | |
| 7 | 2022 | 16 | |
| 8 | 2020 | 15 | |
| 9 | 2021 | 14 | |
| 10 | 2022 | 12 | |
| 11 | 2020 | 11 | |
| 12 | 2023 | 8 | |
| 13 | 2022 | 8 | |
| 14 | 2022 | 8 | |
| 15 | 2022 | 7 | |
| 16 | 2024 | 6 | |
| 17 | 2022 | 6 | |
| 18 | 2022 | 5 | |
| 19 | 2023 | 5 | |
| 20 | 2020 | 4 |
About Lele Ai
Lele Ai is a scholar working on Infectious Diseases, Parasitology, Ecology, Evolution, Behavior and Systematics, Public Health, Environmental and Occupational Health and Genetics, having authored 27 papers that have together received 465 indexed citations. Recurring topics across this work include Viral Infections and Vectors (15 papers), Vector-Borne Animal Diseases (7 papers), Vector-borne infectious diseases (7 papers), COVID-19 epidemiological studies (4 papers), Viral Infections and Outbreaks Research (4 papers), Animal Virus Infections Studies (3 papers), Fire effects on ecosystems (3 papers) and Mosquito-borne diseases and control (3 papers). The work is most often cited by research in Infectious Diseases (330 citations), Animal Science and Zoology (94 citations), Parasitology (57 citations), Modeling and Simulation (34 citations) and Virology (12 citations). Lele Ai has collaborated with scholars based in China, United States and Russia. Frequent co-authors include Changqiang Zhu, Weilong Tan, Dan Hu, Fuqiang Ye, Changjun Wang, Lu Yang, Youjun Feng, Chenxi Ding, Jin Zhu and Ting He. Their work appears in journals such as Scientific Reports, Frontiers in Cellular and Infection Microbiology, BMC Public Health, Frontiers in Public Health and Virus Research.
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.