Fernando Díaz

2.2k total citations
64 papers, 1.2k citations indexed

About

Fernando Díaz is a scholar working on Artificial Intelligence, Industrial and Manufacturing Engineering and Molecular Biology. According to data from OpenAlex, Fernando Díaz has authored 64 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 21 papers in Industrial and Manufacturing Engineering and 12 papers in Molecular Biology. Recurrent topics in Fernando Díaz's work include Vehicle Routing Optimization Methods (18 papers), Metaheuristic Optimization Algorithms Research (16 papers) and Gene expression and cancer classification (9 papers). Fernando Díaz is often cited by papers focused on Vehicle Routing Optimization Methods (18 papers), Metaheuristic Optimization Algorithms Research (16 papers) and Gene expression and cancer classification (9 papers). Fernando Díaz collaborates with scholars based in Spain, United States and Portugal. Fernando Díaz's co-authors include Eneko Osaba, Roberto Carballedo, Florentino Fdez‐Riverola, Pedro López-García, Enrique Onieva, Juan M. Corchado, Xin‐She Yang, José R. Méndez, Asier Perallos and Eva Iglesias and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Fernando Díaz

62 papers receiving 1.2k citations

Peers

Fernando Díaz
Pedro Isasi Spain
Barbara M. Smith United Kingdom
Göran Falkman Sweden
Mehrdad Rostami Finland
Carmelo J. A. Bastos-Filho Brazil
Ralf Klinkenberg Germany
Azuraliza Abu Bakar Malaysia
Josiah Poon Australia
Li Zou China
Xiaofang Chen China
Pedro Isasi Spain
Fernando Díaz
Citations per year, relative to Fernando Díaz Fernando Díaz (= 1×) peers Pedro Isasi

Countries citing papers authored by Fernando Díaz

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Díaz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fernando Díaz

This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Díaz. A scholar is included among the top collaborators of Fernando Díaz 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 Fernando Díaz. Fernando Díaz 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.
Díaz, Fernando & Michael Madaio. (2024). Scaling Laws Do Not Scale. Proceedings of the AAAI/ACM Conference on AI Ethics and Society. 7. 341–357. 5 indexed citations
2.
Capelo, José Luís, Carlos Lodeiro, Rajiv Dhir, et al.. (2023). Pathway-guided monitoring of the disease course in bladder cancer with longitudinal urine proteomics. SHILAP Revista de lepidopterología. 3(1). 8–8. 2 indexed citations
3.
Recio, J. M., et al.. (2017). Characterization of tirsification soil weathering processes: The case of Los Lirios wetland, Guadalquivir basin, Seville, Spain. Chilean journal of agricultural research. 77(4). 406–412. 2 indexed citations
4.
Martínez‐Prieto, Miguel A., et al.. (2017). Towards a Scalable Architecture for Flight Data Management. 263–268. 4 indexed citations
5.
Novoa, Ana M., Julia B. Ward, Davide Malmusi, et al.. (2015). How substandard dwellings and housing affordability problems are associated with poor health in a vulnerable population during the economic recession of the late 2000s. International Journal for Equity in Health. 14(1). 120–120. 35 indexed citations
6.
Osaba, Eneko, Xin‐She Yang, Fernando Díaz, Pedro López-García, & Roberto Carballedo. (2015). An improved discrete bat algorithm for symmetric and asymmetric Traveling Salesman Problems. Engineering Applications of Artificial Intelligence. 48. 59–71. 224 indexed citations
7.
Osaba, Eneko, Enrique Onieva, Fernando Díaz, et al.. (2015). A Migration Strategy For Distributed Evolutionary Algorithms Based On Stopping Non-Promising Subpopulations: A Case Study On Routing Problems. INFM-OAR (INFN Catania). 13(2). 46–56. 15 indexed citations
8.
9.
Osaba, Eneko, Fernando Díaz, Enrique Onieva, Roberto Carballedo, & Asier Perallos. (2014). AMCPA: A Population Metaheuristic With Adaptive Crossover Probability and Multi-Crossover Mechanism for Solving Combinatorial Optimization Problems. TECNALIA Publications (Fundación TECNALIA Research & Innovation). 12(2). 1–23. 17 indexed citations
10.
Osaba, Eneko, Fernando Díaz, & Enrique Onieva. (2013). A novel meta-heuristic based on soccer concepts to solve routing problems. TECNALIA Publications (Fundación TECNALIA Research & Innovation). 1743–1744. 16 indexed citations
11.
Osaba, Eneko & Fernando Díaz. (2012). Comparison of a memetic algorithm and a tabu search algorithm for the traveling salesman problem. TECNALIA Publications (Fundación TECNALIA Research & Innovation). 131–136. 11 indexed citations
12.
Reboiro‐Jato, Miguel, Rosalía Laza, Hugo López-Fernández, et al.. (2012). genEnsemble: A new model for the combination of classifiers and integration of biological knowledge applied to genomic data. Expert Systems with Applications. 40(1). 52–63. 6 indexed citations
13.
Domínguez-Morales, Manuel, et al.. (2010). Frames-to-AER efficiency study based on CPUs performance counters. idUS (Universidad de Sevilla). 141–148. 1 indexed citations
14.
Glez‐Peña, Daniel, Miguel Reboiro‐Jato, Paulo Maia, et al.. (2010). AIBench: A rapid application development framework for translational research in biomedicine. Computer Methods and Programs in Biomedicine. 98(2). 191–203. 28 indexed citations
15.
Glez‐Peña, Daniel, et al.. (2009). DFP: a Bioconductor package for fuzzy profile identification and gene reduction of microarray data. BMC Bioinformatics. 10(1). 37–37. 11 indexed citations
16.
Glez‐Peña, Daniel, Fernando Díaz, Jesús María Hernández‐Rivas, Juan M. Corchado, & Florentino Fdez‐Riverola. (2009). geneCBR: a translational tool for multiple-microarray analysis and integrative information retrieval for aiding diagnosis in cancer research. BMC Bioinformatics. 10(1). 187–187. 18 indexed citations
17.
Lourenço, Anália, Daniel Glez‐Peña, José R. Méndez, et al.. (2009). BioDR: Semantic indexing networks for biomedical document retrieval. Expert Systems with Applications. 37(4). 3444–3453. 12 indexed citations
18.
Méndez, José R., Florentino Fdez‐Riverola, Daniel Glez‐Peña, Fernando Díaz, & Juan M. Corchado. (2007). Relaxing feature selection in spam filtering by using case-based reasoning systems. 53–62. 2 indexed citations
19.
Álvarez, Esther & Fernando Díaz. (2007). Framework for the dynamic scheduling of complex job shops. International Journal of Manufacturing Technology and Management. 11(3/4). 411–411. 6 indexed citations
20.
Méndez, José R., Eva Iglesias, Florentino Fdez‐Riverola, Fernando Díaz, & Juan M. Corchado. (2005). Analyzing the Impact of Corpus Preprocessing on AntiSpam Filtering Software. Research in computing science. 17. 129–138. 4 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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