Hao‐Yuan Cheng
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies 12
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research 9
- COVID-19 Clinical Research Studies 6
- Viral gastroenteritis research and epidemiology 5
- Viral Infections and Outbreaks Research 5
- Clinical Psychology top 10%
- Health top 10%
- Information Systems top 5%
- COVID-19 Digital Contact Tracing 6
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- Data-Driven Disease Surveillance 6
- Influenza Virus Research Studies 4
- Co-authors
- Hsien-Ho LinDing‐Ping LiuShu-Wan JianTa-Chou Vincent NgWan‐Ting HuangMichael G. BakerAmanda KvalsvigLucy Telfar-Barnard
- Journals
- JAMA Internal Medicine (2 papers)Journal of Microbiology Immunology and Infection (2 papers)Vaccine (2 papers)
- Partner nations
- TaiwanUnited StatesUnited Kingdom
In The Last Decade
Hao‐Yuan Cheng
32 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Modeling and Simulation 504
- Infectious Diseases 542
- Clinical Psychology 185
- Health 72
- Information Systems 168
Countries citing papers authored by Hao‐Yuan Cheng
This map shows the geographic impact of Hao‐Yuan 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 Hao‐Yuan Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hao‐Yuan Cheng more than expected).
Fields of papers citing papers by Hao‐Yuan Cheng
This network shows the impact of papers produced by Hao‐Yuan 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 Hao‐Yuan Cheng. The network helps show where Hao‐Yuan Cheng may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Hao‐Yuan 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
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 0 | |
| 2 | 2024 | 7 | |
| 3 | 2023 | 3 | |
| 4 | 2022 | 8 | |
| 5 | 2022 | 10 | |
| 6 | 2022 | 15 | |
| 7 | 2021 | 20 | |
| 8 | 2021 | 3 | |
| 9 | 2020 | 39 | |
| 10 | 2020 | 12 | |
| 11 | 2020 | 22 | |
| 12 | 2020 | 182 | |
| 13 | 2020 | 20 | |
| 14 | 2020 | 89 | |
| 15 | 2018 | 2 | |
| 16 | 2018 | 12 | |
| 17 | 2018 | 2 | |
| 18 | 2017 | 14 | |
| 19 | 2015 | 7 | |
| 20 | 2014 | 37 |
About Hao‐Yuan Cheng
Hao‐Yuan Cheng is a scholar working on Modeling and Simulation, Infectious Diseases and Emergency Medical Services, having authored 33 papers that have together received 1.3k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (12 papers), SARS-CoV-2 and COVID-19 Research (9 papers), COVID-19 Clinical Research Studies (6 papers), COVID-19 Digital Contact Tracing (6 papers), Data-Driven Disease Surveillance (6 papers), Viral gastroenteritis research and epidemiology (5 papers), Viral Infections and Outbreaks Research (5 papers) and Influenza Virus Research Studies (4 papers). The work is most often cited by research in Modeling and Simulation (504 citations), Infectious Diseases (542 citations) and Clinical Psychology (185 citations). Hao‐Yuan Cheng has collaborated with scholars based in Taiwan, United States and United Kingdom. Frequent co-authors include Hsien-Ho Lin, Ding‐Ping Liu, Shu-Wan Jian, Ta-Chou Vincent Ng, Wan‐Ting Huang, Michael G. Baker, Amanda Kvalsvig, Lucy Telfar-Barnard, Jennifer Summers and Nick Wilson. Their work appears in journals such as JAMA Internal Medicine, Journal of Microbiology Immunology and Infection, Vaccine, International Journal of Infectious Diseases and Emerging infectious diseases.
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.