Javier Sánchez‐Monedero

1.6k total citations · 1 hit paper
35 papers, 892 citations indexed

About

Javier Sánchez‐Monedero is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Sociology and Political Science. According to data from OpenAlex, Javier Sánchez‐Monedero has authored 35 papers receiving a total of 892 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 4 papers in Sociology and Political Science. Recurrent topics in Javier Sánchez‐Monedero's work include Neural Networks and Applications (7 papers), Imbalanced Data Classification Techniques (7 papers) and Face and Expression Recognition (6 papers). Javier Sánchez‐Monedero is often cited by papers focused on Neural Networks and Applications (7 papers), Imbalanced Data Classification Techniques (7 papers) and Face and Expression Recognition (6 papers). Javier Sánchez‐Monedero collaborates with scholars based in Spain, United Kingdom and United States. Javier Sánchez‐Monedero's co-authors include César Hervás‐Martínez, Pedro Antonio Gutiérrez, Francisco Fernández‐Navarro, María Pérez‐Ortiz, Lina Dencik, M. Cruz-Ramírez, Lilian Edwards, Aurora Sáez, Sancho Salcedo‐Sanz and C. Casanova‐Mateo and has published in prestigious journals such as Nature Communications, IEEE Transactions on Medical Imaging and Neural Computation.

In The Last Decade

Javier Sánchez‐Monedero

34 papers receiving 867 citations

Hit Papers

Ordinal Regression Methods: Survey and Experimental Study 2015 2026 2018 2022 2015 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Ordinal Regression Methods: Survey and Experimental Study
    2015 281 citations Pedro Antonio Gutiérrez, María Pérez‐Ortiz et al. IEEE Transactions on Knowledge and Data Engineering profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Javier Sánchez‐Monedero Spain 15 450 154 113 94 77 35 892
Roman Kern Austria 19 523 1.2× 123 0.8× 231 2.0× 53 0.6× 52 0.7× 130 1.3k
Been Kim United States 15 1.1k 2.3× 280 1.8× 74 0.7× 29 0.3× 35 0.5× 32 1.5k
Malak Abdullah Jordan 14 670 1.5× 97 0.6× 191 1.7× 146 1.6× 43 0.6× 50 1.2k
Indro Spinelli Italy 7 435 1.0× 83 0.5× 76 0.7× 18 0.2× 56 0.7× 10 939
Bogumił Kamiński Poland 18 215 0.5× 59 0.4× 85 0.8× 49 0.5× 40 0.5× 77 1.4k
Md. Saddam Hossain Mukta Bangladesh 14 420 0.9× 119 0.8× 87 0.8× 65 0.7× 51 0.7× 56 880
Paul Koch United States 10 659 1.5× 195 1.3× 92 0.8× 39 0.4× 30 0.4× 20 1.3k
Maad M. Mıjwıl Iraq 19 375 0.8× 89 0.6× 175 1.5× 14 0.1× 47 0.6× 109 1.3k
Eduardo M. Pereira Portugal 4 601 1.3× 87 0.6× 54 0.5× 23 0.2× 45 0.6× 8 1.0k
Matloob Khushi Australia 20 737 1.6× 78 0.5× 139 1.2× 183 1.9× 81 1.1× 56 1.5k

Countries citing papers authored by Javier Sánchez‐Monedero

Since Specialization
Citations

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

Fields of papers citing papers by Javier Sánchez‐Monedero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Javier Sánchez‐Monedero. 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 Javier Sánchez‐Monedero. The network helps show where Javier Sánchez‐Monedero may publish in the future.

Co-authorship network of co-authors of Javier Sánchez‐Monedero

This figure shows the co-authorship network connecting the top 25 collaborators of Javier Sánchez‐Monedero. A scholar is included among the top collaborators of Javier Sánchez‐Monedero 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 Javier Sánchez‐Monedero. Javier Sánchez‐Monedero 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.
Sánchez‐Monedero, Javier, et al.. (2024). AI research assistants, intrinsic values, and the science we want. AI & Society. 40(1). 235–237. 4 indexed citations
2.
Jansen, Fieke, Javier Sánchez‐Monedero, & Lina Dencik. (2021). Biometric identity systems in law enforcement and the politics of (voice) recognition: The case of SiiP. Big Data & Society. 8(2). 8 indexed citations
3.
Monedero, Pablo, Eva E. Álvarez-León, Miguel A. Hernán, et al.. (2021). A population-based controlled experiment assessing the epidemiological impact of digital contact tracing. Nature Communications. 12(1). 587–587. 82 indexed citations
4.
Sánchez‐Monedero, Javier, Pedro Antonio Gutiérrez, & María Pérez‐Ortiz. (2019). ORCA: A Matlab/Octave Toolbox for Ordinal Regression. Journal of Machine Learning Research. 20(125). 1–5. 11 indexed citations
5.
Sánchez‐Monedero, Javier, María Pérez‐Ortiz, Aurora Sáez, Pedro Antonio Gutiérrez, & César Hervás‐Martínez. (2017). Partial order label decomposition approaches for melanoma diagnosis. Applied Soft Computing. 64. 341–355. 16 indexed citations
6.
Gutiérrez, Pedro Antonio, María Pérez‐Ortiz, Javier Sánchez‐Monedero, & César Hervás‐Martínez. (2016). Representing ordinal input variables in the context of ordinal classification. ORCA Online Research @Cardiff (Cardiff University). 3 indexed citations
7.
Gutiérrez, Pedro Antonio, María Pérez‐Ortiz, Javier Sánchez‐Monedero, Francisco Fernández‐Navarro, & César Hervás‐Martínez. (2015). Ordinal Regression Methods: Survey and Experimental Study. IEEE Transactions on Knowledge and Data Engineering. 28(1). 127–146. 281 indexed citations breakdown →
8.
Pérez‐Ortiz, María, Pedro Antonio Gutiérrez, Javier Sánchez‐Monedero, & César Hervás‐Martínez. (2015). A Study on Multi-Scale Kernel Optimisation via Centered Kernel-Target Alignment. Neural Processing Letters. 44(2). 491–517. 5 indexed citations
9.
Sánchez‐Monedero, Javier, Sancho Salcedo‐Sanz, Pedro Antonio Gutiérrez, C. Casanova‐Mateo, & César Hervás‐Martínez. (2014). Simultaneous modelling of rainfall occurrence and amount using a hierarchical nominal–ordinal support vector classifier. Engineering Applications of Artificial Intelligence. 34. 199–207. 32 indexed citations
10.
Cruz-Ramírez, M., César Hervás‐Martínez, Javier Sánchez‐Monedero, & Pedro Antonio Gutiérrez. (2014). Metrics to guide a multi-objective evolutionary algorithm for ordinal classification. Neurocomputing. 135. 21–31. 63 indexed citations
11.
Sánchez‐Monedero, Javier, et al.. (2014). A guided data projection technique for classification of sovereign ratings: The case of European Union 27. Applied Soft Computing. 22. 339–350. 10 indexed citations
12.
Pérez‐Ortiz, María, Pedro Antonio Gutiérrez, Javier Sánchez‐Monedero, & César Hervás‐Martínez. (2013). Multi-scale Support Vector Machine Optimization by Kernel Target-Alignment.. The European Symposium on Artificial Neural Networks. 1 indexed citations
13.
Sánchez‐Monedero, Javier, Pedro Antonio Gutiérrez, Peter Tiňo, & César Hervás‐Martínez. (2013). Exploitation of Pairwise Class Distances for Ordinal Classification. Neural Computation. 25(9). 2450–2485. 21 indexed citations
14.
Cruz-Ramírez, M., César Hervás‐Martínez, Javier Sánchez‐Monedero, & Pedro Antonio Gutiérrez. (2011). A preliminary study of ordinal metrics to guide a multi-objective evolutionary algorithm. 1176–1181. 17 indexed citations
15.
Sánchez‐Monedero, Javier, et al.. (2011). Bloom filter-based discovery protocol for DDS middleware. Journal of Parallel and Distributed Computing. 71(10). 1305–1317. 18 indexed citations
16.
Fernández‐Navarro, Francisco, César Hervás‐Martínez, Javier Sánchez‐Monedero, & Pedro Antonio Gutiérrez. (2011). MELM-GRBF: A modified version of the extreme learning machine for generalized radial basis function neural networks. Neurocomputing. 74(16). 2502–2510. 58 indexed citations
17.
Sánchez‐Monedero, Javier, Pedro Antonio Gutiérrez, Francisco Fernández‐Navarro, & César Hervás‐Martínez. (2011). Weighting Efficient Accuracy and Minimum Sensitivity for Evolving Multi-Class Classifiers. Neural Processing Letters. 34(2). 101–116. 18 indexed citations
18.
Gutiérrez, Pedro Antonio, et al.. (2011). Evaluating nominal and ordinal classifiers for wind speed prediction from synoptic pressure patterns. 13. 1265–1270. 3 indexed citations
19.
Cruz-Ramírez, M., Javier Sánchez‐Monedero, Francisco Fernández‐Navarro, Juan Carlos Fernández Fernández, & César Hervás‐Martínez. (2010). Memetic pareto differential evolutionary artificial neural networks to determine growth multi-classes in predictive microbiology. Evolutionary Intelligence. 3(3-4). 187–199. 19 indexed citations
20.
Cruz-Ramírez, M., Juan Carlos Fernández Fernández, Javier Sánchez‐Monedero, et al.. (2010). Ensemble determination using the TOPSIS decision support system in multi-objective evolutionary neural network classifiers. 3177. 513–518.

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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