M. Rosa

32 papers receiving 312 citations

Peers

M. Rosa
Comparison fields: 5 of 61
  • Modeling and Simulation 103
  • Statistical and Nonlinear Physics 139
  • Numerical Analysis 38
  • Geometry and Topology 32
  • Mathematical Physics 27
Replace Kaushik Dehingia with:
Kaushik Dehingia India
Konstantin E. Starkov Mexico
Minaya Villasana Venezuela
Wanli Wang China
Janet Dyson Italy
Ritu Agarwal India
Khadijeh Sadri Cyprus
Rosanna Villella-Bressan Italy
Piotr Gwiazda Poland
Kewang Chen China
M. Rosa relative to Kaushik Dehingia India Kaushik Dehingia's profile →
Citations per field
00.5×10×20×25.5×
Kaushik Dehingia · 1×
Citations per year

Countries citing papers authored by M. Rosa

Since Specialization
Citations

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

Fields of papers citing papers by M. Rosa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside M. Rosa, 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 M. Rosa Line = papers co-authored together M. Rosa links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202034
2 201632
3 202026
4 202117
5 201215
6 201515
7 202012
8 201611
9 202011
10 201511
11 202210
12 201510
13 201410
14 20189
15 20169
16 20229
17 20199
18 20228
19 20168
20 20177

About M. Rosa

M. Rosa is a scholar working on Statistical and Nonlinear Physics, Public Health, Environmental and Occupational Health, Modeling and Simulation, Molecular Biology and Mathematical Physics, having authored 34 papers that have together received 324 indexed citations. Recurring topics across this work include Nonlinear Waves and Solitons (16 papers), Nonlinear Photonic Systems (11 papers), Mathematical and Theoretical Epidemiology and Ecology Models (9 papers), Fractional Differential Equations Solutions (7 papers), Mathematical Biology Tumor Growth (5 papers), Advanced Mathematical Physics Problems (5 papers), Single-cell and spatial transcriptomics (3 papers) and CAR-T cell therapy research (3 papers). The work is most often cited by research in Modeling and Simulation (103 citations), Statistical and Nonlinear Physics (139 citations), Numerical Analysis (38 citations), Geometry and Topology (32 citations) and Mathematical Physics (27 citations). M. Rosa has collaborated with scholars based in Spain, Italy and Russia. Frequent co-authors include M.L. Gandarias, M. S. Bruzón, Victor M. Pérez-Garcı́a, Antonio Pérez‐Martínez, Alvaro A. Martinez, Manuel Ramı́rez, Fernando León-Saavedra, Rita Tracinà, Isaac Elishakoff and Maria Lippiello. Their work appears in journals such as Journal of Computational and Applied Mathematics, Communications in Nonlinear Science and Numerical Simulation, Mathematical Methods in the Applied Sciences, Chaos Solitons & Fractals and Clinical & Translational Oncology.

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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