M. Caicedo

601 citations
8 papers · 464 · h-index 6

Impact in

Papers in

M. Caicedo

8 papers receiving 455 citations

Peers

M. Caicedo
Comparison fields: 5 of 47
  • Statistics, Probability and Uncertainty 90
  • Statistical and Nonlinear Physics 158
  • Mechanics of Materials 310
  • Computational Theory and Mathematics 108
  • Computational Mechanics 89
Replace A. Ferrer with:
A. Ferrer Spain
Étienne Prulière France
Edward A.W. Maunder United Kingdom
Annika Robens‐Radermacher Germany
D. Néron France
Diego Hayashi Alonso Brazil
Robert Eggersmann Germany
Marcus Rüter Germany
Matthias Leuschner Germany
Zheng Lv China
M. Caicedo relative to A. Ferrer Spain A. Ferrer's profile →
Citations per field
00.5×10×14.5×
A. Ferrer · 1×
Citations per year

Countries citing papers authored by M. Caicedo

Since Specialization
Citations

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

Fields of papers citing papers by M. Caicedo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside M. Caicedo, 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. Caicedo Line = papers co-authored together M. Caicedo links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 2014145
2 2016124
3 201694
4 201570
5 201821
6
High-performance model reduction procedures in multiscale simulations
20125
7 20144
8 20161

About M. Caicedo

M. Caicedo is a scholar working on Mechanics of Materials, Statistical and Nonlinear Physics, Computational Mechanics, Computational Theory and Mathematics and Civil and Structural Engineering, having authored 8 papers that have together received 464 indexed citations. Recurring topics across this work include Numerical methods in engineering (5 papers), Composite Material Mechanics (5 papers), Model Reduction and Neural Networks (3 papers), Rock Mechanics and Modeling (3 papers), Advanced Mathematical Modeling in Engineering (2 papers), Advanced Numerical Methods in Computational Mathematics (2 papers), Fatigue and fracture mechanics (1 paper) and Structural Health Monitoring Techniques (1 paper). The work is most often cited by research in Statistics, Probability and Uncertainty (90 citations), Statistical and Nonlinear Physics (158 citations), Mechanics of Materials (310 citations), Computational Theory and Mathematics (108 citations) and Computational Mechanics (89 citations). M. Caicedo has collaborated with scholars based in Spain, Argentina and France. Frequent co-authors include J.A. Hernández, Alfredo E. Huespe, J. Oliver, A. Ferrer, J. Cante, Emmanuel Roubin, Sebastián Toro, Marcelo Raschi and O. Lloberas‐Valls. Their work appears in journals such as Computer Methods in Applied Mechanics and Engineering, Archives of Computational Methods in Engineering, Key engineering materials and Conicet.

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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