Fernando Casas

3.8k citations
125 papers · 2.1k · h-index 26

Impact in

Papers in

Fernando Casas

114 papers receiving 2.0k citations

Peers

Fernando Casas
Comparison fields: 5 of 108
  • Numerical Analysis 816
  • Statistical and Nonlinear Physics 416
  • Modeling and Simulation 109
  • Computational Theory and Mathematics 329
  • Gastroenterology 79
Replace Harry Pollard with:
Harry Pollard United States
Sergio Blanes Spain
Joaquin B. Diaz United States
J. A. C. Weideman South Africa
Charles W. Groetsch United States
Loukas Grafakos United States
Peter R. Graves-Morris United Kingdom
Leonid Aronovich Knizhnerman United States
Avram Sidi Israel
Brynjulf Owren Norway
Fernando Casas relative to Harry Pollard United States Harry Pollard's profile →
Citations per field
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Citations per year

Countries citing papers authored by Fernando Casas

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Casas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 125 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016122
2 2001100
3 199897
4 201278
5 200071
6 201365
7 201260
8 200460
9 201055
10 201354
11 200254
12 200654
13 201752
14 200751
15 200949
16 201347
17 199943
18 201441
19 201238
20 200337

About Fernando Casas

Fernando Casas is a scholar working on Numerical Analysis, Statistical and Nonlinear Physics, Computational Theory and Mathematics, Computational Mechanics and Modeling and Simulation, having authored 125 papers that have together received 2.1k indexed citations. Recurring topics across this work include Numerical methods for differential equations (80 papers), Matrix Theory and Algorithms (25 papers), Electromagnetic Simulation and Numerical Methods (24 papers), Advanced Numerical Methods in Computational Mathematics (17 papers), Differential Equations and Numerical Methods (13 papers), Quantum chaos and dynamical systems (12 papers), Mechanical Circulatory Support Devices (11 papers) and Computational Fluid Dynamics and Aerodynamics (10 papers). The work is most often cited by research in Numerical Analysis (816 citations), Statistical and Nonlinear Physics (416 citations), Modeling and Simulation (109 citations), Computational Theory and Mathematics (329 citations) and Gastroenterology (79 citations). Fernando Casas has collaborated with scholars based in Spain, United States and Austria. Frequent co-authors include Sergio Blanes, Ander Murua, J.M. Gómez-Ros, José-Angel Oteo, J Ros, Philipp Bader, Arieh Iserles, Vicente Martı́nez, Jacques Laskar and Ariadna Farrés. Their work appears in journals such as Journal of Computational and Applied Mathematics, Applied Numerical Mathematics, ASAIO Journal, Artificial Organs and Applied Mathematics and Computation.

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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