Daihai He
- Modeling and Simulation top 0.02%
- Infectious Diseases top 0.2%
- Public Health, Environmental and Occupational Health top 0.5%
- Economics and Econometrics top 0.5%
- Epidemiology top 2%
- Co-authors
- Shi ZhaoSalihu S. MusaLin YangDaozhou GaoYijun LouMaggie Haitian WangWeiming WangQianying Lin
- Topics
- COVID-19 epidemiological studies (136 papers)SARS-CoV-2 and COVID-19 Research (63 papers)Influenza Virus Research Studies (35 papers)
- Cited by
- Modeling and SimulationInfectious DiseasesPublic Health, Environmental and Occupational Health
- Journals
- Proceedings of the National Academy of SciencesPhysical Review LettersSHILAP Revista de lepidopterología
- Partner nations
- Hong KongChinaUnited States
In The Last Decade
Daihai He
218 papers receiving 6.6k citations
Hit Papers
Peers
Comparison fields: 5 of 182
- Modeling and Simulation 4.0k
- Infectious Diseases 3.0k
- Public Health, Environmental and Occupational Health 1.6k
- Economics and Econometrics 1.2k
- Epidemiology 1.0k
Countries citing papers authored by Daihai He
This map shows the geographic impact of Daihai He'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 Daihai He with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daihai He more than expected).
Fields of papers citing papers by Daihai He
This network shows the impact of papers produced by Daihai He. 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 Daihai He. The network helps show where Daihai He may publish in the future.
Co-authorship network of co-authors of Daihai He
This figure shows the co-authorship network connecting the top 25 collaborators of Daihai He. A scholar is included among the top collaborators of Daihai He based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daihai He. Daihai He is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | 8 | |
| 9 | 10 | |
| 10 | 7 | |
| 11 | 5 | |
| 12 | 15 | |
| 13 | 23 | |
| 14 | 1 | |
| 15 | 2 | |
| 16 | 67 | |
| 17 | 24 | |
| 18 | 21 | |
| 19 | 29 | |
| 20 | 15 |
About Daihai He
Daihai He is a scholar working on Modeling and Simulation, Infectious Diseases and Statistical and Nonlinear Physics, having authored 225 papers that have together received 6.8k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (136 papers), SARS-CoV-2 and COVID-19 Research (63 papers) and Influenza Virus Research Studies (35 papers). The work is most often cited by research in Modeling and Simulation (4.0k citations), Infectious Diseases (3.0k citations) and Public Health, Environmental and Occupational Health (1.6k citations). Daihai He has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Shi Zhao, Salihu S. Musa, Lin Yang, Daozhou Gao, Yijun Lou, Maggie Haitian Wang, Weiming Wang, Qianying Lin, Jinjun Ran and Guangpu Yang. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and SHILAP Revista de lepidopterología.
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.