Thomas Giletti

22 papers receiving 369 citations

Peers

Thomas Giletti
Comparison fields: 5 of 38
  • Modeling and Simulation 149
  • Public Health, Environmental and Occupational Health 339
  • Applied Mathematics 98
  • Numerical Analysis 49
  • Genetics 184
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Xiongxiong Bao China
Shuxia Pan China
Weihua Ruan United States
Guo‐Bao Zhang China
Yukio Kan-on Japan
Ying Su China
Narcisa Apreutesei Romania
Yaping Wu China
Wenjie Zuo China
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Citations per year

Countries citing papers authored by Thomas Giletti

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Giletti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside Thomas Giletti, 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 Thomas Giletti Line = papers co-authored together Thomas Giletti links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201477
2 201956
3 201841
4 201235
5 202128
6 201323
7 201917
8 201914
9 201413
10 201713
11 202112
12 201512
13 201310
14 20228
15 20218
16 20157
17 20104
18 20223
19 20212
20 20222

About Thomas Giletti

Thomas Giletti is a scholar working on Public Health, Environmental and Occupational Health, Applied Mathematics, Genetics, Computer Networks and Communications and Modeling and Simulation, having authored 24 papers that have together received 388 indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (23 papers), Evolution and Genetic Dynamics (9 papers), Nonlinear Differential Equations Analysis (7 papers), Mathematical Biology Tumor Growth (7 papers), Nonlinear Dynamics and Pattern Formation (7 papers), Differential Equations and Numerical Methods (5 papers), Stochastic processes and statistical mechanics (3 papers) and Stability and Controllability of Differential Equations (3 papers). The work is most often cited by research in Modeling and Simulation (149 citations), Public Health, Environmental and Occupational Health (339 citations), Applied Mathematics (98 citations), Numerical Analysis (49 citations) and Genetics (184 citations). Thomas Giletti has collaborated with scholars based in France, Japan and Taiwan. Frequent co-authors include Arnaud Ducrot, Hiroshi Matano, Jong‐Shenq Guo, Matthieu Alfaro, Luca Rossi, Jimmy Garnier, Lionel Roques, Maolin Zhou, Weiwei Ding and Xinfu Chen. Their work appears in journals such as Calculus of Variations and Partial Differential Equations, Journal of Mathematical Biology, Nonlinear Differential Equations and Applications NoDEA, Discrete and Continuous Dynamical Systems - S and Journal de Mathématiques Pures et Appliquées.

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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