Pilar M. Ortigosa

1.4k total citations
90 papers, 911 citations indexed

About

Pilar M. Ortigosa is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Organizational Behavior and Human Resource Management. According to data from OpenAlex, Pilar M. Ortigosa has authored 90 papers receiving a total of 911 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 18 papers in Computational Theory and Mathematics and 17 papers in Organizational Behavior and Human Resource Management. Recurrent topics in Pilar M. Ortigosa's work include Facility Location and Emergency Management (17 papers), Solar Thermal and Photovoltaic Systems (15 papers) and Vehicle Routing Optimization Methods (15 papers). Pilar M. Ortigosa is often cited by papers focused on Facility Location and Emergency Management (17 papers), Solar Thermal and Photovoltaic Systems (15 papers) and Vehicle Routing Optimization Methods (15 papers). Pilar M. Ortigosa collaborates with scholars based in Spain, United Kingdom and Lithuania. Pilar M. Ortigosa's co-authors include Juana L. Redondo, I. García, José Fernández, J.D. Álvarez, Manuel Berenguel, N.C. Cruz, Márk Jelasity, Eduardo Camponogara, Julio E. Normey‐Rico and Eva M. Ortigosa and has published in prestigious journals such as SHILAP Revista de lepidopterología, Renewable and Sustainable Energy Reviews and Scientific Reports.

In The Last Decade

Pilar M. Ortigosa

84 papers receiving 880 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pilar M. Ortigosa Spain 18 276 194 181 167 156 90 911
Juana L. Redondo Spain 17 200 0.7× 191 1.0× 160 0.9× 168 1.0× 139 0.9× 71 782
Akash Tayal India 11 169 0.6× 25 0.1× 32 0.2× 80 0.5× 177 1.1× 29 680
D.V. Tošić Serbia 13 72 0.3× 18 0.1× 143 0.8× 66 0.4× 232 1.5× 44 604
Buyang Cao China 14 146 0.5× 19 0.1× 13 0.1× 120 0.7× 291 1.9× 39 707
Federico Malucelli Italy 23 74 0.3× 14 0.1× 45 0.2× 200 1.2× 466 3.0× 111 1.9k
P Kumar India 11 161 0.6× 9 0.0× 17 0.1× 30 0.2× 134 0.9× 35 764
Weisheng Xu China 14 77 0.3× 22 0.1× 28 0.2× 62 0.4× 59 0.4× 82 697
Tandra Pal India 18 336 1.2× 10 0.1× 19 0.1× 34 0.2× 88 0.6× 56 1.1k
Chou‐Yuan Lee Taiwan 13 362 1.3× 8 0.0× 16 0.1× 55 0.3× 203 1.3× 32 973
Claudio Gambella Ireland 8 149 0.5× 10 0.1× 10 0.1× 115 0.7× 97 0.6× 8 696

Countries citing papers authored by Pilar M. Ortigosa

Since Specialization
Citations

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

Fields of papers citing papers by Pilar M. Ortigosa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pilar M. Ortigosa

This figure shows the co-authorship network connecting the top 25 collaborators of Pilar M. Ortigosa. A scholar is included among the top collaborators of Pilar M. Ortigosa 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 Pilar M. Ortigosa. Pilar M. Ortigosa 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.
Ortigosa, Pilar M., et al.. (2025). Privacy-aware fall detection and alert management in smart environments using multimodal devices. Internet of Things. 30. 101526–101526. 1 indexed citations
2.
Cruz, N.C., et al.. (2025). A holistic approach for resource-constrained neural network architecture search. Applied Soft Computing. 172. 112832–112832.
3.
Redondo, Juana L., et al.. (2024). ALMERIA: Boosting Pairwise Molecular Contrasts with Scalable Methods. Informatica. 617–648.
4.
Redondo, Juana L., et al.. (2024). Bi-Level Optimization to Enhance Intensity Modulated Radiation Therapy Planning. Informatica. 99–124. 1 indexed citations
5.
Cruciani, Federico, et al.. (2024). Data Augmentation for Human Activity Recognition With Generative Adversarial Networks. IEEE Journal of Biomedical and Health Informatics. 28(4). 2350–2361. 12 indexed citations
6.
Medina-Quero, Javier, et al.. (2023). 3D Human Pose Estimation from multi-view thermal vision sensors. Information Fusion. 104. 102154–102154. 14 indexed citations
7.
8.
Cruz, N.C., et al.. (2019). COLLABORATIVE PROJECT-BASED LEARNING: AN EXPERIENCE. EDULEARN proceedings. 1. 8631–8635. 2 indexed citations
9.
Ferrández, Miriam R., Juana L. Redondo, Benjamín Ivorra, Ángel Ramos, & Pilar M. Ortigosa. (2019). Preference-based multi-objectivization applied to decision support for High-Pressure Thermal processes in food treatment. Applied Soft Computing. 79. 326–340. 12 indexed citations
10.
Fernández, José, Boglárka G.-Tóth, Juana L. Redondo, & Pilar M. Ortigosa. (2018). The probabilistic customer’s choice rule with a threshold attraction value: Effect on the location of competitive facilities in the plane. Computers & Operations Research. 101. 234–249. 22 indexed citations
11.
Cruz, N.C., Saı̈d Salhi, Juana L. Redondo, et al.. (2018). Design of a parallel genetic algorithm for continuous and pattern-free heliostat field optimization. The Journal of Supercomputing. 75(3). 1268–1283. 12 indexed citations
12.
Cruz, N.C., J.D. Álvarez, Juana L. Redondo, Manuel Berenguel, & Pilar M. Ortigosa. (2018). A two-layered solution for automatic heliostat aiming. Engineering Applications of Artificial Intelligence. 72. 253–266. 19 indexed citations
13.
Cruz, N.C., et al.. (2016). High performance computing for the heliostat field layout evaluation. The Journal of Supercomputing. 73(1). 259–276. 16 indexed citations
14.
Redondo, Juana L., José Fernández, & Pilar M. Ortigosa. (2016). FEMOEA: a fast and efficient multi-objective evolutionary algorithm. Mathematical Methods of Operations Research. 85(1). 113–135. 6 indexed citations
15.
Redondo, Juana L., et al.. (2014). Approximating the Pareto-front of a planar bi-objective competitive facility location and design problem. Computers & Operations Research. 62. 337–349. 31 indexed citations
16.
Redondo, Juana L., Pilar M. Ortigosa, & Julius Žilinskas. (2012). Multimodal Evolutionary Algorithm for Multidimensional Scaling with City-Block Distances. Informatica. 23(4). 601–620. 7 indexed citations
17.
Ortigosa, Pilar M., et al.. (2011). DESIGN OF CLIL ACTIVITIES FOR COMPUTER ENGINEERING COURSES AT THE UNIVERSITY. EDULEARN proceedings. 32(7). 2311–2319. 1 indexed citations
18.
Redondo, Juana L., Blas Pelegrı́n, Pascual Fernández, I. García, & Pilar M. Ortigosa. (2010). Finding multiple global optima for unconstrained discrete location problems. Optimization methods & software. 26(2). 207–224. 3 indexed citations
19.
Ortigosa, Pilar M., Juana L. Redondo, I. García, & José‐Jesús Fernández. (2006). A population global optimization algorithm to solve the image alignment problem in electron crystallography. Journal of Global Optimization. 37(4). 527–539. 8 indexed citations
20.
Ortigosa, Pilar M., János Balogh, & I. García. (1999). A parallelized sequential random search global optimization algorithm. Acta Cybernetica. 14(2). 403–418. 2 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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