M.J. Rubio

426 citations
19 papers · 315 · h-index 8

Impact in

Papers in

M.J. Rubio

18 papers receiving 304 citations

Peers

M.J. Rubio
Comparison fields: 5 of 27
  • Numerical Analysis 299
  • Modeling and Simulation 114
  • Computational Theory and Mathematics 180
  • Mathematical Physics 40
  • Computational Mechanics 31
Replace M. A. Salanova with:
M. A. Salanova Spain
Miquel Grau-Sánchez Spain
Sergio Plaza Chile
Izhar Uddin India
C. L. E. Moore Nigeria
Hafiz Fukhar-ud-din Saudi Arabia
Bashir Ali Nigeria
Grey Ercole Brazil
Juhana Siljander Finland
Nicola Abatangelo Germany
M.J. Rubio relative to M. A. Salanova Spain M. A. Salanova's profile →
Citations per field
00.5×
M. A. Salanova · 1×
Citations per year

Countries citing papers authored by M.J. Rubio

Since Specialization
Citations

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

Fields of papers citing papers by M.J. Rubio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside M.J. Rubio, 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.J. Rubio Line = papers co-authored together M.J. Rubio links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 200072
2 200251
3 200244
4 200238
5 200530
6 200121
7 200312
8 20148
9 20157
10 20177
11 19995
12 20185
13 20155
14 20163
15 20132
16 20192
17
Aneurismas cerebrales: estudio mediante TC-helicoidal (angio-TC) con reconstrucciones tridimensionales.
19991
18
El método de Newton: de Newton a Kantorovich
20101
19 20161

About M.J. Rubio

M.J. Rubio is a scholar working on Numerical Analysis, Modeling and Simulation, Mathematical Physics, Computational Theory and Mathematics and Computational Mechanics, having authored 19 papers that have together received 315 indexed citations. Recurring topics across this work include Iterative Methods for Nonlinear Equations (18 papers), Advanced Optimization Algorithms Research (12 papers), Fractional Differential Equations Solutions (9 papers), Matrix Theory and Algorithms (5 papers), Numerical methods in inverse problems (5 papers), Advanced Numerical Analysis Techniques (1 paper), Mathematical and Theoretical Analysis (1 paper) and Statistical and numerical algorithms (1 paper). The work is most often cited by research in Numerical Analysis (299 citations), Modeling and Simulation (114 citations), Computational Theory and Mathematics (180 citations), Mathematical Physics (40 citations) and Computational Mechanics (31 citations). M.J. Rubio has collaborated with scholars based in Spain, United States and Colombia. Frequent co-authors include J.A. Ezquerro, M.A. Hernández, Sergio Amat, Á. Alberto Magreñán, Ioannis K. Argyros, Sonia Busquier, J.M. Gutiérrez, José Manuel García Montes, Juan Carlos Galán and M.C. Merino. Their work appears in journals such as Applied Mathematics and Computation, Journal of Computational and Applied Mathematics, Numerical Algorithms, Applied Mathematics Letters and Numerical Functional Analysis and Optimization.

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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