Ying‐Hen Hsieh

3.4k citations
87 papers · 2.5k indexed · h-index 26
Topics
COVID-19 epidemiological studies (35 papers)Mathematical and Theoretical Epidemiology and Ecology Models (20 papers)Influenza Virus Research Studies (16 papers)
Partner nations
TaiwanChinaUnited States

In The Last Decade

Ying‐Hen Hsieh

87 papers receiving 2.3k citations

Peers

Ying‐Hen Hsieh
Comparison fields: 5 of 153
  • Modeling and Simulation 968
  • Public Health, Environmental and Occupational Health 936
  • Epidemiology 629
  • Infectious Diseases 483
  • Genetics 427
Replace Maciej F. Boni with:
Maciej F. Boni United Kingdom
Benjamín Roche France
Shweta Bansal United States
Nicholas C. Grassly United Kingdom
Matthew J. Ferrari United States
Suzanne Lenhart United States
F. Ellis McKenzie United States
Katherine E. Atkins United Kingdom
Cláudia Torres Codeço Brazil
Andrea Pugliese Italy
Ying‐Hen Hsieh relative to Maciej F. Boni United Kingdom Maciej F. Boni's profile →
Citations per field
00.5×1.5×
Maciej F. Boni · 1×
Citations per year

Countries citing papers authored by Ying‐Hen Hsieh

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Ying‐Hen Hsieh

This figure shows the co-authorship network connecting the top 25 collaborators of Ying‐Hen Hsieh. A scholar is included among the top collaborators of Ying‐Hen Hsieh 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 Ying‐Hen Hsieh. Ying‐Hen Hsieh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 8
3 24
4 4
5 8
6 4
7 2
8 3
9 6
10 40
11 14
12 9
13 25
14 109
15 30
16 14
17 53
18 48
19 8
20 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) and Influenza Virus Research Studies (16 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.

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