Ying‐Hen Hsieh
- Modeling and Simulation top 0.2%
- COVID-19 epidemiological studies 35
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- Mathematical and Theoretical Epidemiology and Ecology Models 20
- Mosquito-borne diseases and control 9
- Infectious Diseases top 5%
- HIV/AIDS Research and Interventions 9
- Viral Infections and Vectors 8
- Ecological Modeling top 5%
- Hepatology top 5%
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- Influenza Virus Research Studies 16
- HIV, Drug Use, Sexual Risk 11
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- Evolution and Genetic Dynamics 10
- Co-authors
- Cathy W. S. ChenBernard D. ColemanPaul GeorgescuMichael A. MaresMichael R. WilligChengjun SunStefan MaJorge X. Velasco‐Hernández
- Cited by
- Modeling and SimulationPublic Health, Environmental and Occupational HealthInfectious Diseases
- Journals
- Proceedings of the National Academy of Sciences (1 paper)Applied Physics Letters (1 paper)PLoS ONE (6 papers)
- Partner nations
- TaiwanChinaUnited States
In The Last Decade
Ying‐Hen Hsieh
87 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 153
- Modeling and Simulation 968
- Public Health, Environmental and Occupational Health 936
- Infectious Diseases 483
- Ecological Modeling 108
- Hepatology 175
Countries citing papers authored by Ying‐Hen Hsieh
This map shows the geographic impact of Ying‐Hen Hsieh'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 Ying‐Hen Hsieh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying‐Hen Hsieh more than expected).
Fields of papers citing papers by Ying‐Hen Hsieh
This network shows the impact of papers produced by Ying‐Hen Hsieh. 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 Ying‐Hen Hsieh. The network helps show where Ying‐Hen Hsieh may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ying‐Hen Hsieh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2017 | 8 | |
| 3 | 2017 | 24 | |
| 4 | 2015 | 4 | |
| 5 | 2015 | 8 | |
| 6 | 2013 | 4 | |
| 7 | 2011 | 2 | |
| 8 | 2011 | 3 | |
| 9 | 2011 | 6 | |
| 10 | 2010 | 40 | |
| 11 | 2010 | 14 | |
| 12 | 2010 | 9 | |
| 13 | 2009 | 25 | |
| 14 | 2008 | 109 | |
| 15 | 2007 | 30 | |
| 16 | 2006 | 14 | |
| 17 | 2006 | 53 | |
| 18 | 2003 | 48 | |
| 19 | 2002 | 8 | |
| 20 | 1995 | 15 |
About Ying‐Hen Hsieh
Ying‐Hen Hsieh is a scholar working on Modeling and Simulation, Infectious Diseases and Virology, having authored 87 papers that have together received 2.5k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (35 papers), Mathematical and Theoretical Epidemiology and Ecology Models (20 papers), Influenza Virus Research Studies (16 papers), HIV, Drug Use, Sexual Risk (11 papers), Evolution and Genetic Dynamics (10 papers), Mosquito-borne diseases and control (9 papers), HIV/AIDS Research and Interventions (9 papers) and Viral Infections and Vectors (8 papers). The work is most often cited by research in Modeling and Simulation (968 citations), Public Health, Environmental and Occupational Health (936 citations) and Infectious Diseases (483 citations). Ying‐Hen Hsieh has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Cathy W. S. Chen, Bernard D. Coleman, Paul Georgescu, Michael A. Mares, Michael R. Willig, Chengjun Sun, Stefan Ma, Jorge X. Velasco‐Hernández, Sze-Bi Hsu and Jian Wu. Their work appears in journals such as Proceedings of the National Academy of Sciences, Applied Physics Letters and PLoS ONE.
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.