L. Jódar

3.9k total citations
290 papers, 2.9k citations indexed

About

L. Jódar is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Applied Mathematics. According to data from OpenAlex, L. Jódar has authored 290 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 163 papers in Numerical Analysis, 105 papers in Computational Theory and Mathematics and 98 papers in Applied Mathematics. Recurrent topics in L. Jódar's work include Numerical methods for differential equations (101 papers), Differential Equations and Numerical Methods (94 papers) and Matrix Theory and Algorithms (81 papers). L. Jódar is often cited by papers focused on Numerical methods for differential equations (101 papers), Differential Equations and Numerical Methods (94 papers) and Matrix Theory and Algorithms (81 papers). L. Jódar collaborates with scholars based in Spain, Colombia and United States. L. Jódar's co-authors include J.‐C. Cortés, Emilio Defez, L. Villafuerte, Gilberto González‐Parra, Rafael J. Villanueva, Abraham J. Arenas, Jorge Sastre, Francisco José Santonja Gómez, Pablo Sevilla‐Peris and Paloma Merello and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Automatic Control and Sustainability.

In The Last Decade

L. Jódar

272 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
L. Jódar Spain	24	929	899	868	669	570	290	2.9k
J.‐C. Cortés Spain	20	471 0.5×	394 0.4×	289 0.3×	577 0.9×	394 0.7×	200	1.8k
Lorenzo Pareschi Italy	35	1.8k 2.0×	289 0.3×	563 0.6×	498 0.7×	912 1.6×	147	4.4k
Martino Bardi Italy	21	929 1.0×	1.2k 1.4×	419 0.5×	366 0.5×	353 0.6×	60	3.0k
R. Z. Khas’minskiĭ United States	27	519 0.6×	566 0.6×	281 0.3×	735 1.1×	672 1.2×	85	4.3k
Adem Kılıçman Malaysia	32	1.4k 1.6×	521 0.6×	1.7k 2.0×	2.4k 3.5×	907 1.6×	421	4.6k
G.S. Ladde United States	19	1.3k 1.3×	395 0.4×	1.1k 1.2×	435 0.7×	154 0.3×	115	2.3k
Giuseppe Toscani Italy	42	2.7k 2.9×	774 0.9×	218 0.3×	1.1k 1.6×	2.0k 3.5×	201	5.8k
L. C. Evans United States	25	1.4k 1.5×	1.2k 1.4×	378 0.4×	269 0.4×	320 0.6×	34	2.9k
Jiongmin Yong United States	37	1.1k 1.2×	1.4k 1.6×	489 0.6×	848 1.3×	291 0.5×	164	6.3k
John S. Maybee United States	17	1.4k 1.5×	1.5k 1.7×	552 0.6×	246 0.4×	189 0.3×	67	3.3k

Countries citing papers authored by L. Jódar

Since Specialization

Citations

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

Fields of papers citing papers by L. Jódar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of L. Jódar

This figure shows the co-authorship network connecting the top 25 collaborators of L. Jódar. A scholar is included among the top collaborators of L. Jódar 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 L. Jódar. L. Jódar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Jódar, L., et al.. (2024). A random free-boundary diffusive logistic differential model: Numerical analysis, computing and simulation. Mathematics and Computers in Simulation. 221. 55–78. 1 indexed citations

Jódar, L., et al.. (2018). A Local Radial Basis Function Method for High-Dimensional American Option Pricing Problems. Mathematical Modelling and Analysis. 23(1). 117–138. 11 indexed citations

Braumann, Carlos A., J.‐C. Cortés, L. Jódar, & L. Villafuerte. (2017). On the random gamma function: Theory and computing. Journal of Computational and Applied Mathematics. 335. 142–155. 9 indexed citations

Cortés, J.‐C., L. Jódar, & L. Villafuerte. (2015). Laguerre random differential polynomials: definition, differential and statistical properties. RiuNet (Politechnical University of Valencia). 98. 283–293. 6 indexed citations

Jódar, L., et al.. (2013). Positive Solutions of European Option Pricing with CGMY Process Models Using Double Discretization Difference Schemes. Abstract and Applied Analysis. 2013. 1–11. 1 indexed citations

Jódar, L., et al.. (2007). Computing the variable coefficient telegraph equation using a discrete eigenfunctions method. Computers & Mathematics with Applications. 54(3). 448–458. 21 indexed citations

Solís, Francisco J. & L. Jódar. (2004). Nonisolated slow convergence in discrete dynamical systems. Applied Mathematics Letters. 17(5). 597–599. 4 indexed citations

Jódar, L., et al.. (2003). Convergent discrete numerical solutions of strongly coupled mixed parabolic systems. 63. 151–172.

Rodríguez-Álvarez, María José, et al.. (2003). Exact solution of variable coefficient mixed hyperbolic partial differential problems. Applied Mathematics Letters. 16(3). 309–312. 1 indexed citations

10.

Jódar, L. & J.‐C. Cortés. (2000). Closed form general solution of the hypergeometric matrix differential equation. Mathematical and Computer Modelling. 32(9). 1017–1028. 46 indexed citations

11.

Jódar, L., et al.. (1996). Orthogonal matrix polynomials with respect to linear matrix moment functionals: Theory and applications. Approximation Theory and Its Applications. 12(1). 96–115. 21 indexed citations

12.

Jódar, L., et al.. (1995). A matrix constructive method for the analytic-numerical solution of coupled partial differential systems. Applications of Mathematics. 40(5). 391–400. 1 indexed citations

13.

Padgett, George A., et al.. (1995). Inheritance of histiocytosis in Bernese mountain dogs. Journal of Small Animal Practice. 36(3). 93–98. 48 indexed citations

14.

Jódar, L.. (1994). Boundary value problems for coupled systems of second order differential equations with a singularity of the first kind: explicit solutions. Applications of Mathematics. 39(1). 1–13. 1 indexed citations

15.

Jódar, L., et al.. (1992). Solución de sistemas acoplados de ecuaciones en diferencias de segundo orden sin aumentar la dimensión del problema. Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería. 8(3). 207–214. 1 indexed citations

16.

Jódar, L., et al.. (1991). Resolución Numérica de sistemas acoplados de ecuaciones en derivadas parciales. Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería. 7(3). 289–300. 2 indexed citations

17.

Jódar, L., et al.. (1990). Solución de problemas de contorno para ecuaciones en diferencias matriciales de segundo orden. Revista Internacional de Métodos Numéricos para Cálculo y Diseño en Ingeniería. 6(3). 397–408. 1 indexed citations

18.

Jódar, L.. (1986). Algebraic methods for solving boundary value problems.. 10(3). 259–270.

19.

Jódar, L.. (1985). On strictly cyclic operator algebras.. 9(1). 87–90. 1 indexed citations

20.

Jódar, L.. (1985). Ecuaciones diferenciales matriciales con dos condiciones de contorno. Revista de la Unión Matemática Argentina. 32(1). 29–40. 1 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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