M.‐D. Roselló

876 total citations
68 papers, 676 citations indexed

About

M.‐D. Roselló is a scholar working on Statistics, Probability and Uncertainty, Statistical and Nonlinear Physics and Numerical Analysis. According to data from OpenAlex, M.‐D. Roselló has authored 68 papers receiving a total of 676 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Statistics, Probability and Uncertainty, 15 papers in Statistical and Nonlinear Physics and 14 papers in Numerical Analysis. Recurrent topics in M.‐D. Roselló's work include Probabilistic and Robust Engineering Design (26 papers), Differential Equations and Numerical Methods (12 papers) and Fractional Differential Equations Solutions (8 papers). M.‐D. Roselló is often cited by papers focused on Probabilistic and Robust Engineering Design (26 papers), Differential Equations and Numerical Methods (12 papers) and Fractional Differential Equations Solutions (8 papers). M.‐D. Roselló collaborates with scholars based in Spain, United States and Egypt. M.‐D. Roselló's co-authors include J.‐V. Romero, J.‐C. Cortés, F.J. Salvador, Joaquín Martínez‐López, David Jaramillo, Rafael J. Villanueva, L. Jódar, Benito M. Chen‐Charpentier, Francisco José Arnau and J.-A. Moraño and has published in prestigious journals such as Journal of the Franklin Institute, Chaos Solitons & Fractals and Applied Mathematics and Computation.

In The Last Decade

M.‐D. Roselló

65 papers receiving 653 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.‐D. Roselló Spain 14 209 157 130 128 100 68 676
J.‐V. Romero Spain 14 232 1.1× 146 0.9× 107 0.8× 128 1.0× 89 0.9× 61 699
Mohammad Khalil United States 15 131 0.6× 185 1.2× 24 0.2× 62 0.5× 75 0.8× 45 472
Mazen Saad France 15 569 2.7× 16 0.1× 157 1.2× 24 0.2× 58 0.6× 69 956
Gahl Berkooz Sweden 2 365 1.7× 118 0.8× 9 0.1× 20 0.2× 324 3.2× 2 606
Fuad S. Alduais Saudi Arabia 13 166 0.8× 50 0.3× 77 0.6× 21 0.2× 23 0.2× 89 569
R. Redlinger Germany 12 134 0.6× 82 0.5× 78 0.6× 81 0.6× 5 0.1× 37 526
M. F. Dimentberg United States 19 115 0.6× 561 3.6× 59 0.5× 6 0.0× 380 3.8× 72 1.2k
José Camberos United States 15 388 1.9× 148 0.9× 6 0.0× 30 0.2× 127 1.3× 101 909
J. D. Rodríguez Spain 13 147 0.7× 46 0.3× 6 0.0× 70 0.5× 164 1.6× 34 569
Hyung‐Chun Lee South Korea 12 367 1.8× 108 0.7× 16 0.1× 14 0.1× 219 2.2× 42 550

Countries citing papers authored by M.‐D. Roselló

Since Specialization
Citations

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

Fields of papers citing papers by M.‐D. Roselló

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M.‐D. Roselló

This figure shows the co-authorship network connecting the top 25 collaborators of M.‐D. Roselló. A scholar is included among the top collaborators of M.‐D. Roselló 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.‐D. Roselló. M.‐D. Roselló 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.
Cortés, J.‐C., et al.. (2024). Probabilistic analysis of the steady state of weakly perturbed linear oscillators subject to a class of Gaussian inputs. Chaos Solitons & Fractals. 187. 115451–115451.
2.
Cortés, J.‐C., et al.. (2021). Solving fully randomized higher‐order linear control differential equations: Application to study the dynamics of an oscillator. Computational and Mathematical Methods. 3(6). 1 indexed citations
3.
Cortés, J.‐C., et al.. (2020). Introducing randomness in the analysis of chemical reactions: An analysis based on random differential equations and probability density functions. Computational and Mathematical Methods. 3(6). 2 indexed citations
4.
5.
Cortés, J.‐C., et al.. (2019). A probabilistic analysis of a Beverton-Holt-type discrete model: Theoretical and computing analysis. Computational and Mathematical Methods. 1(1). e1013–e1013. 2 indexed citations
6.
7.
Cortés, J.‐C., et al.. (2018). Some results about randomized binary Markov chains: theory, computing and applications. International Journal of Computer Mathematics. 97(1-2). 141–156. 6 indexed citations
8.
9.
Cortés, J.‐C., et al.. (2017). Computing the two first probability density functions of the random Cauchy-Euler differential equation: Study about regular-singular points. Applied Mathematics and Nonlinear Sciences. 2(1). 213–224. 4 indexed citations
10.
Romero, J.‐V., et al.. (2016). Approximating the Solution Stochastic Process of the Random Cauchy One-Dimensional Heat Model. Abstract and Applied Analysis. 2016. 1–7. 5 indexed citations
11.
Cortés, J.‐C., et al.. (2016). Probabilistic solution of random autonomous first-order linear systems of ordinary differential equations. RiuNet (Politechnical University of Valencia). 68(4). 1397–1406. 7 indexed citations
12.
Cortés, J.‐C., et al.. (2016). Computing probabilistic solutions of the Bernoulli random differential equation. Journal of Computational and Applied Mathematics. 309. 396–407. 13 indexed citations
13.
Salvador, F.J., David Jaramillo, J.‐V. Romero, & M.‐D. Roselló. (2016). Using a homogeneous equilibrium model for the study of the inner nozzle flow and cavitation pattern in convergent–divergent nozzles of diesel injectors. Journal of Computational and Applied Mathematics. 309. 630–641. 32 indexed citations
14.
Salvador, F.J., J.‐V. Romero, M.‐D. Roselló, & David Jaramillo. (2015). Numerical simulation of primary atomization in diesel spray at low injection pressure. Journal of Computational and Applied Mathematics. 291. 94–102. 43 indexed citations
15.
Chen‐Charpentier, Benito M., J.‐C. Cortés, J.‐V. Romero, & M.‐D. Roselló. (2013). Do the generalized polynomial chaos and Fröbenius methods retain the statistical moments of random differential equations?. Applied Mathematics Letters. 26(5). 553–558. 2 indexed citations
16.
Salvador, F.J., Joaquín Martínez‐López, J.‐V. Romero, & M.‐D. Roselló. (2010). Influence of biofuels on the internal flow in diesel injector nozzles. Mathematical and Computer Modelling. 54(7-8). 1699–1705. 24 indexed citations
17.
Chen‐Charpentier, Benito M., L. Jódar, & M.‐D. Roselló. (2007). Constructing accurate polynomial approximations for nonlinear differential initial value problems. Applied Mathematics and Computation. 193(2). 523–534. 3 indexed citations
18.
Roselló, M.‐D., et al.. (2005). An iterative method to obtain analytical-numerical approximation of the one-dimensional gas flow transport solution in conical ducts. Mathematical and Computer Modelling. 41(4-5). 407–416. 2 indexed citations
19.
Roselló, M.‐D., et al.. (2004). A collocation method to compute one-dimensional flow models in intake and exhaust systems of internal combustion engines. Mathematical and Computer Modelling. 40(9-10). 995–1008. 3 indexed citations
20.
Jódar, L., et al.. (2003). The truncation error of the two-variable chebyshev series expansions. Computers & Mathematics with Applications. 45(10-11). 1647–1653. 9 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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