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
- Parasitology top 10%
- Vector-borne infectious diseases
Papers in
-
- Viral Infections and Vectors 13
- Viral Infections and Outbreaks Research 3
- Parasitology 10
- Vector-borne infectious diseases 8
- Co-authors
- Weilong Tan (25 shared papers)Changqiang Zhu (24 shared papers)Dan Hu (4 shared papers)Fuqiang Ye (7 shared papers)Lu Yang (4 shared papers)Changjun Wang (4 shared papers)Youjun Feng (2 shared papers)Jin Zhu (2 shared papers)
- Journals
- Scientific Reports (4 papers)Frontiers in Cellular and Infection Microbiology (3 papers)Frontiers in Public Health (2 papers)BMC Public Health (2 papers)Frontiers in Genetics (1 paper)
- Partner nations
- ChinaRussiaUnited States
In The Last Decade
Lele Ai
26 papers receiving 492 citations
Peers
Comparison fields: 5 of 76
- Infectious Diseases 321
- Parasitology 63
- Animal Science and Zoology 93
- Modeling and Simulation 32
- 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 198 | |
| 2 | 2017 | 50 | |
| 3 | 2023 | 30 | |
| 4 | 2021 | 29 | |
| 5 | 2022 | 22 | |
| 6 | 2020 | 17 | |
| 7 | 2022 | 17 | |
| 8 | 2020 | 15 | |
| 9 | 2021 | 15 | |
| 10 | 2022 | 12 | |
| 11 | 2020 | 12 | |
| 12 | 2023 | 10 | |
| 13 | 2024 | 10 | |
| 14 | 2022 | 9 | |
| 15 | 2022 | 8 | |
| 16 | 2022 | 8 | |
| 17 | 2022 | 8 | |
| 18 | 2023 | 6 | |
| 19 | 2022 | 6 | |
| 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 Animal Science and Zoology, having authored 28 papers that have together received 499 indexed citations. Recurring topics across this work include Viral Infections and Vectors (13 papers), Vector-borne infectious diseases (8 papers), Vector-Borne Animal Diseases (6 papers), Mosquito-borne diseases and control (3 papers), Viral Infections and Outbreaks Research (3 papers), Animal Virus Infections Studies (3 papers), Climate Change and Health Impacts (2 papers) and Fire effects on ecosystems (2 papers). The work is most often cited by research in Infectious Diseases (321 citations), Parasitology (63 citations), Animal Science and Zoology (93 citations), Modeling and Simulation (32 citations) and Virology (12 citations). Lele Ai has collaborated with scholars based in China, Russia and United States. Frequent co-authors include Weilong Tan, Changqiang Zhu, Dan Hu, Fuqiang Ye, Lu Yang, Changjun Wang, Youjun Feng, Jin Zhu, Chenxi Ding and Ting He. Their work appears in journals such as Scientific Reports, Frontiers in Cellular and Infection Microbiology, Frontiers in Public Health, BMC Public Health and Frontiers in Genetics.
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.