Fernando Casas

3.1k citations
115 papers · 1.9k · h-index 25

Impact in

Papers in

Fernando Casas

107 papers receiving 1.8k citations

Peers

Fernando Casas
Comparison fields: 5 of 102
  • Numerical Analysis 781
  • Statistical and Nonlinear Physics 382
  • Modeling and Simulation 106
  • Computational Theory and Mathematics 299
  • Computational Mechanics 327
Replace Sergio Blanes with:
Sergio Blanes Spain
J. A. C. Weideman South Africa
John P. Coleman United Kingdom
J. N. Lyness United States
Folkmar Bornemann Germany
Avram Sidi Israel
Hans Munthe–Kaas Norway
C. W. Groetsch United States
Leonid Knizhnerman Russia
Loukas Grafakos United States
Fernando Casas relative to Sergio Blanes Spain Sergio Blanes's profile →
Citations per field
00.5×1.5×
Sergio Blanes · 1×
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 115 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016109
2 199895
3 200195
4 200074
5 201272
6 201255
7 201355
8 201054
9 200453
10 200251
11 200750
12 201346
13 201344
14 200844
15 200644
16 200942
17 201442
18 201238
19 199938
20 200637

About Fernando Casas

Fernando Casas is a scholar working on Numerical Analysis, Statistical and Nonlinear Physics, Electrical and Electronic Engineering, Computational Mechanics and Computational Theory and Mathematics, having authored 115 papers that have together received 1.9k indexed citations. Recurring topics across this work include Numerical methods for differential equations (73 papers), Matrix Theory and Algorithms (23 papers), Electromagnetic Simulation and Numerical Methods (22 papers), Advanced Numerical Methods in Computational Mathematics (15 papers), Differential Equations and Numerical Methods (13 papers), Mechanical Circulatory Support Devices (11 papers), Quantum chaos and dynamical systems (11 papers) and Computational Fluid Dynamics and Aerodynamics (10 papers). The work is most often cited by research in Numerical Analysis (781 citations), Statistical and Nonlinear Physics (382 citations), Modeling and Simulation (106 citations), Computational Theory and Mathematics (299 citations) and Computational Mechanics (327 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, J A Oteo, J Ros, Philipp Bader, Arieh Iserles, Ariadna Farrés, J. Laskar and Celso Grebogi. Their work appears in journals such as Journal of Computational and Applied Mathematics, Applied Numerical Mathematics, Artificial Organs, ASAIO Journal and SIAM Journal on Scientific Computing.

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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