Yun Kang

3.1k citations
121 papers · 2.3k indexed · 1 hit paper · h-index 27
Topics
Mathematical and Theoretical Epidemiology and Ecology Models (68 papers)Evolution and Genetic Dynamics (55 papers)Plant and animal studies (29 papers)
Partner nations
United StatesChinaIndia

In The Last Decade

Yun Kang

110 papers receiving 2.2k citations

Hit Papers

A stochastic SIRS epidemic model with infectious force un...2015202620182022201550100150200250

Peers

Yun Kang
Comparison fields: 5 of 116
  • Public Health, Environmental and Occupational Health 1.6k
  • Genetics 1.4k
  • Modeling and Simulation 870
  • Sociology and Political Science 408
  • Ecology, Evolution, Behavior and Systematics 351
Replace Frithjof Lutscher with:
Frithjof Lutscher Canada
Frank M. Hilker Germany
Xinyu Song China
Malay Banerjee India
Alison Gray United Kingdom
G. P. Samanta India
Michel Langlais France
Lionel Roques France
Joydev Chattopadhyay India
Maia Martcheva United States
Yun Kang relative to Frithjof Lutscher Canada Frithjof Lutscher's profile →
Citations per field
00.5×1.5×
Frithjof Lutscher · 1×
Citations per year

Countries citing papers authored by Yun Kang

Since Specialization
Citations

This map shows the geographic impact of Yun Kang'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 Yun Kang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yun Kang more than expected).

Fields of papers citing papers by Yun Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yun Kang. 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 Yun Kang. The network helps show where Yun Kang may publish in the future.

Co-authorship network of co-authors of Yun Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Yun Kang. A scholar is included among the top collaborators of Yun Kang 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 Yun Kang. Yun Kang 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 0
2 0
3 0
4 1
5 0
6 5
7 5
8 25
9 20
10 15
11 5
12 14
13 27
14 6
15
A stochastic SIRS epidemic model with infectious force under intervention strategiesbreakdown →
286
16 24
17 37
18 26
19 15
20 40

About Yun Kang

Yun Kang is a scholar working on Modeling and Simulation, Genetics and Public Health, Environmental and Occupational Health, having authored 121 papers that have together received 2.3k indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (68 papers), Evolution and Genetic Dynamics (55 papers) and Plant and animal studies (29 papers). The work is most often cited by research in Modeling and Simulation (870 citations), Public Health, Environmental and Occupational Health (1.6k citations) and Genetics (1.4k citations). Yun Kang has collaborated with scholars based in United States, China and India. Frequent co-authors include Yongli Cai, Weiming Wang, Malay Banerjee, Carlos Castillo‐Chávez, Feng Rao, Pankaj Kumar Tiwari, Sourav Kumar Sasmal, Peng Feng, Dieter Armbruster and Gloria DeGrandi‐Hoffman. Their work appears in journals such as SHILAP Revista de lepidopterología, Proceedings of the Royal Society B Biological Sciences and Molecular Ecology.

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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