Qu Cheng
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Ecological Modeling top 10%
Papers in
-
- Viral Infections and Vectors 6
-
- Mosquito-borne diseases and control 8
- Co-authors
- Peng Gong (4 shared papers)Justin V. Remais (10 shared papers)Song Liang (7 shared papers)Robert C. Spear (5 shared papers)Qinlong Jing (3 shared papers)John M. Marshall (2 shared papers)Zhicong Yang (2 shared papers)Baoguo Jiang (1 shared paper)
- Journals
- PLoS neglected tropical diseases (4 papers)Proceedings of the National Academy of Sciences (2 papers)BMC Infectious Diseases (2 papers)PLoS Computational Biology (2 papers)International Journal of Remote Sensing (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Qu Cheng
34 papers receiving 708 citations
Peers
Comparison fields: 5 of 123
- Modeling and Simulation 58
- Ecological Modeling 29
- Transportation 44
- Infectious Diseases 104
- Global and Planetary Change 126
Countries citing papers authored by Qu Cheng
This map shows the geographic impact of Qu Cheng'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 Qu Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qu Cheng more than expected).
Fields of papers citing papers by Qu Cheng
This network shows the impact of papers produced by Qu Cheng. 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 Qu Cheng. The network helps show where Qu Cheng may publish in the future.
Co-authors
The 25 scholars most cited alongside Qu Cheng, 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 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 171 | |
| 2 | 2017 | 126 | |
| 3 | 2016 | 82 | |
| 4 | 2019 | 41 | |
| 5 | 2020 | 36 | |
| 6 | 2019 | 29 | |
| 7 | 2017 | 27 | |
| 8 | 2022 | 25 | |
| 9 | 2021 | 21 | |
| 10 | 2024 | 18 | |
| 11 | 2020 | 14 | |
| 12 | 2020 | 13 | |
| 13 | 2021 | 12 | |
| 14 | 2021 | 12 | |
| 15 | 2008 | 12 | |
| 16 | 2019 | 11 | |
| 17 | 2021 | 11 | |
| 18 | 2023 | 9 | |
| 19 | 2021 | 8 | |
| 20 | 2024 | 7 |
About Qu Cheng
Qu Cheng is a scholar working on Infectious Diseases, Public Health, Environmental and Occupational Health, Civil and Structural Engineering, Electrical and Electronic Engineering and Health, Toxicology and Mutagenesis, having authored 38 papers that have together received 726 indexed citations. Recurring topics across this work include Mosquito-borne diseases and control (8 papers), Viral Infections and Vectors (6 papers), COVID-19 epidemiological studies (4 papers), Air Quality and Health Impacts (3 papers), Climate Change and Health Impacts (3 papers), Data-Driven Disease Surveillance (2 papers), Species Distribution and Climate Change (2 papers) and Vibration and Dynamic Analysis (2 papers). The work is most often cited by research in Modeling and Simulation (58 citations), Ecological Modeling (29 citations), Transportation (44 citations), Infectious Diseases (104 citations) and Global and Planetary Change (126 citations). Qu Cheng has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Peng Gong, Justin V. Remais, Song Liang, Robert C. Spear, Qinlong Jing, John M. Marshall, Zhicong Yang, Baoguo Jiang, Morgan Levy and Tianbing Wang. Their work appears in journals such as PLoS neglected tropical diseases, Proceedings of the National Academy of Sciences, BMC Infectious Diseases, PLoS Computational Biology and International Journal of Remote Sensing.
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.