Michael Y. Li

7.6k citations
63 papers · 5.7k indexed · 4 hit papers · h-index 33

Impact in

Papers in

Michael Y. Li

62 papers receiving 5.3k citations

Hit Papers

Why is it difficult to accurately predict the COVID-19 epidemic? 2020 · 392 citations
3921995202620052015200400600

Peers

Michael Y. Li
Comparison fields: 5 of 133
  • Modeling and Simulation 3.0k
  • Public Health, Environmental and Occupational Health 3.8k
  • Genetics 2.1k
  • Statistical and Nonlinear Physics 708
  • Virology 251
Replace Sanyi Tang with:
Sanyi Tang China
Wendi Wang China
Odo Diekmann Netherlands
Horst R. Thieme United States
Xingfu Zou Canada
Linda J. S. Allen United States
James Watmough Canada
Hal L. Smith United States
Herbert W. Hethcote United States
Xiao‐Qiang Zhao Canada
Michael Y. Li relative to Sanyi Tang China Sanyi Tang's profile →
Citations per field
00.5×1.5×1.8×
Sanyi Tang · 1×
Citations per year

Countries citing papers authored by Michael Y. Li

Since Specialization
Citations

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

Fields of papers citing papers by Michael Y. Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Y. Li. 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 Michael Y. Li. The network helps show where Michael Y. Li may publish in the future.

Co-authors

The 25 scholars most cited alongside Michael Y. Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Y. Li Line = papers co-authored together Michael Y. Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20223
2 20226
3 20216
4 202116
5 202112
6 202048
7 202036
8
Why is it difficult to accurately predict the COVID-19 epidemic?
Hit paper breakdown →
2020392
9 20177
10 201132
11 201082
12 2009168
13
Global-stability problem for coupled systems of differential equations on networks
Hit paper breakdown →
2009703
14 200955
15 200830
16 200265
17 200131
18 200039
19 199860
20 199621

About Michael Y. Li

Michael Y. Li is a scholar working on Modeling and Simulation, Virology, Public Health, Environmental and Occupational Health, Geometry and Topology and Genetics, having authored 63 papers that have together received 5.7k indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (31 papers), Evolution and Genetic Dynamics (21 papers), COVID-19 epidemiological studies (18 papers), Advanced Differential Equations and Dynamical Systems (8 papers), Nonlinear Dynamics and Pattern Formation (8 papers), T-cell and Retrovirus Studies (6 papers), HIV Research and Treatment (6 papers) and Immune Cell Function and Interaction (6 papers). The work is most often cited by research in Modeling and Simulation (3.0k citations), Public Health, Environmental and Occupational Health (3.8k citations), Genetics (2.1k citations), Statistical and Nonlinear Physics (708 citations) and Virology (251 citations). Michael Y. Li has collaborated with scholars based in Canada, China and United States. Frequent co-authors include James S. Muldowney, Zhisheng Shuai, Liancheng Wang, Hongying Shu, Hongbin Guo, János Karsai, John R. Graef, Weston Roda, Junjie Wei and Marie Varughese. Their work appears in journals such as Mathematical Biosciences, Bulletin of Mathematical Biology, SIAM Journal on Applied Mathematics, Journal of Mathematical Analysis and Applications and Journal of Differential Equations.

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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