M.J. Ibáñez

520 total citations
51 papers, 380 citations indexed

About

M.J. Ibáñez is a scholar working on Computational Mechanics, Mechanics of Materials and Numerical Analysis. According to data from OpenAlex, M.J. Ibáñez has authored 51 papers receiving a total of 380 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Computational Mechanics, 16 papers in Mechanics of Materials and 13 papers in Numerical Analysis. Recurrent topics in M.J. Ibáñez's work include Advanced Numerical Analysis Techniques (32 papers), Numerical methods in engineering (15 papers) and Iterative Methods for Nonlinear Equations (11 papers). M.J. Ibáñez is often cited by papers focused on Advanced Numerical Analysis Techniques (32 papers), Numerical methods in engineering (15 papers) and Iterative Methods for Nonlinear Equations (11 papers). M.J. Ibáñez collaborates with scholars based in Spain, Morocco and France. M.J. Ibáñez's co-authors include D. Barrera, D. Sbibih, Paul Sablonnière, J.B. Roldán, P. González, Allal Guessab, R. J. Yáñez, Amr El Abbadi, F. Jiménez-Molinos and Catterina Dagnino and has published in prestigious journals such as IEEE Access, IEEE Transactions on Electron Devices and Applied Mathematics and Computation.

In The Last Decade

M.J. Ibáñez

47 papers receiving 371 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
M.J. Ibáñez Spain 12 254 126 115 73 48 51 380
D. Barrera Spain 14 286 1.1× 132 1.0× 116 1.0× 100 1.4× 44 0.9× 65 458
Xiaohong Zhu China 7 172 0.7× 36 0.3× 73 0.6× 25 0.3× 10 0.2× 11 311
Eugeniusz Zieniuk Poland 11 143 0.6× 19 0.2× 196 1.7× 59 0.8× 4 0.1× 51 295
Erich Hartmann Germany 12 352 1.4× 22 0.2× 13 0.1× 14 0.2× 5 0.1× 25 461
Nicolas Neuß Germany 7 273 1.1× 34 0.3× 115 1.0× 51 0.7× 2 0.0× 11 397
Jiřı́ Felcman Czechia 10 291 1.1× 127 1.0× 34 0.3× 38 0.5× 1 0.0× 25 361
R. M. Loy United States 5 143 0.6× 50 0.4× 12 0.1× 40 0.5× 2 0.0× 7 249
Christiane Pöschl Austria 5 122 0.5× 19 0.2× 34 0.3× 18 0.2× 6 236
U. Diewald Germany 5 356 1.4× 9 0.1× 17 0.1× 6 0.1× 2 0.0× 8 435
Hong Oh Kim South Korea 11 74 0.3× 9 0.1× 7 0.1× 4 0.1× 69 1.4× 44 302

Countries citing papers authored by M.J. Ibáñez

Since Specialization
Citations

This map shows the geographic impact of M.J. Ibáñez'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. Ibáñez 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. Ibáñez more than expected).

Fields of papers citing papers by M.J. Ibáñez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M.J. Ibáñez

This figure shows the co-authorship network connecting the top 25 collaborators of M.J. Ibáñez. A scholar is included among the top collaborators of M.J. Ibáñez based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with M.J. Ibáñez. M.J. Ibáñez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Barrera, D., et al.. (2025). Multinode Shepard functions and tensor product polynomial interpolation: Applications to Digital Elevation Models. Journal of Computational and Applied Mathematics. 475. 117036–117036.
2.
3.
Barrera, D., et al.. (2023). Low-degree spline quasi-interpolants in the Bernstein basis. Applied Mathematics and Computation. 457. 128150–128150. 3 indexed citations
4.
López, Francisco Javier Ariza, et al.. (2022). Spline quasi‐interpolation in the Bernstein basis and its application to digital elevation models. Mathematical Methods in the Applied Sciences. 46(2). 1687–1698. 5 indexed citations
5.
Ibáñez, M.J., D. Barrera, D. Maldonado, R. J. Yáñez, & J.B. Roldán. (2021). Non-Uniform Spline Quasi-Interpolation to Extract the Series Resistance in Resistive Switching Memristors for Compact Modeling Purposes. Mathematics. 9(17). 2159–2159. 10 indexed citations
6.
Ibáñez, M.J., et al.. (2021). Quasi-Interpolation in a Space of C2 Sextic Splines over Powell–Sabin Triangulations. Mathematics. 9(18). 2276–2276. 2 indexed citations
7.
Barrera, D., et al.. (2018). Quasi-interpolation by C1 quartic splines on type-1 triangulations. Journal of Computational and Applied Mathematics. 349. 225–238. 8 indexed citations
8.
Barrera, D., et al.. (2018). Point and differential C1 quasi-interpolation on three direction meshes. Journal of Computational and Applied Mathematics. 354. 373–389. 8 indexed citations
9.
Barrera, D., et al.. (2017). A spline quasi-interpolation based method to obtain the reset voltage in Resistive RAMs in the charge-flux domain. Journal of Computational and Applied Mathematics. 354. 326–333. 9 indexed citations
10.
Barrera, D., et al.. (2016). Polynomial pattern finding in scattered data. Journal of Computational and Applied Mathematics. 318. 107–116. 3 indexed citations
11.
Barrera, D., et al.. (2016). On the construction of trivariate near-best quasi-interpolants based on C2 quartic splines on type-6 tetrahedral partitions. Journal of Computational and Applied Mathematics. 311. 252–261. 7 indexed citations
12.
Barrera, D. & M.J. Ibáñez. (2015). Hermite spline interpolation on a three direction mesh from Powell–Sabin and Hsieh–Clough–Tocher finite elements. Journal of Computational and Applied Mathematics. 318. 565–579. 2 indexed citations
13.
Barrera, D., et al.. (2014). A general spline differential quadrature method based on quasi-interpolation. Journal of Computational and Applied Mathematics. 275. 465–479. 14 indexed citations
14.
Barrera, D., et al.. (2014). On spline-based differential quadrature. Journal of Computational and Applied Mathematics. 275. 272–280. 6 indexed citations
15.
Barrera, D., et al.. (2013). Increasing the approximation order of spline quasi-interpolants. Journal of Computational and Applied Mathematics. 252. 27–39. 14 indexed citations
16.
Barrera, D., et al.. (2012). Construction techniques for multivariate modified quasi-interpolants with high approximation order. Computers & Mathematics with Applications. 65(1). 29–41. 4 indexed citations
17.
Abbadi, Amr El, D. Barrera, M.J. Ibáñez, & D. Sbibih. (2010). A general method for constructing quasi-interpolants from B-splines. Journal of Computational and Applied Mathematics. 234(4). 1324–1337. 13 indexed citations
18.
Barrera, D., M.J. Ibáñez, Paul Sablonnière, & D. Sbibih. (2009). On near-best discrete quasi-interpolation on a four-directional mesh. Journal of Computational and Applied Mathematics. 233(6). 1470–1477. 20 indexed citations
19.
Barrera, D., M.J. Ibáñez, Paul Sablonnière, & D. Sbibih. (2005). Near-best quasi-interpolants associated with H-splines on a three-direction mesh. Journal of Computational and Applied Mathematics. 183(1). 133–152. 23 indexed citations
20.
Barrera, D., M.J. Ibáñez, Paul Sablonnière, & D. Sbibih. (2004). Near minimally normed spline quasi-interpolants on uniform partitions. Journal of Computational and Applied Mathematics. 181(1). 211–233. 19 indexed citations

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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