Jorge Díez

1.8k total citations
58 papers, 1.2k citations indexed

About

Jorge Díez is a scholar working on Artificial Intelligence, Information Systems and Biomedical Engineering. According to data from OpenAlex, Jorge Díez has authored 58 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 12 papers in Information Systems and 11 papers in Biomedical Engineering. Recurrent topics in Jorge Díez's work include Genetic and phenotypic traits in livestock (9 papers), Text and Document Classification Technologies (7 papers) and Recommender Systems and Techniques (5 papers). Jorge Díez is often cited by papers focused on Genetic and phenotypic traits in livestock (9 papers), Text and Document Classification Technologies (7 papers) and Recommender Systems and Techniques (5 papers). Jorge Díez collaborates with scholars based in Spain, United States and China. Jorge Díez's co-authors include Juan José del Coz, Antonio Bahamonde, Oscar Luaces, José Barranquero Tolosa, F. Goyache, L. J. Royo, I. Álvarez, I. Fernández, Juan Pablo Gutiérrez and Pablo González and has published in prestigious journals such as Trends in Food Science & Technology, Expert Systems with Applications and Energy.

In The Last Decade

Jorge Díez

54 papers receiving 1.1k citations

Peers

Jorge Díez

GENET

CVPR

ASZ

Paul Kwan Australia

Md. Shahjalal South Korea

Daniel Smith Australia

Dong Sun Park South Korea

Zhou Fang China

Sook Yoon South Korea

Diego H. Milone Argentina

Santosh Kumar India

Philip Valencia Australia

Tingting Liang China

Paul Kwan Australia

Jorge Díez

208 ×0.6

253 ×1.0

GENET

246 ×1.7

CVPR

61 ×0.4

116 ×0.9

ASZ

Citations per year, relative to Jorge Díez Jorge Díez (= 1×) peers Paul Kwan

Countries citing papers authored by Jorge Díez

Since Specialization

Citations

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

Fields of papers citing papers by Jorge Díez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jorge Díez

This figure shows the co-authorship network connecting the top 25 collaborators of Jorge Díez. A scholar is included among the top collaborators of Jorge Díez 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 Jorge Díez. Jorge Díez 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

Rodríguez, E., et al.. (2025). Modeling biodiesel properties by preference learning: Case study of cetane number. Engineering Applications of Artificial Intelligence. 144. 110107–110107. 1 indexed citations

Müller, Michael, et al.. (2025). AUDIT: An open-source Python library for AI model evaluation with use cases in MRI brain tumor segmentation. Computer Methods and Programs in Biomedicine. 271. 108991–108991.

Díez, Jorge, et al.. (2024). P3 - Anomaly Detection of Rotating and Oscillating Bearings using Autoencoder. 127–130. 1 indexed citations

Díez, Jorge, et al.. (2024). A multi-task framework for breast cancer segmentation and classification in ultrasound imaging. Computer Methods and Programs in Biomedicine. 260. 108540–108540. 8 indexed citations

Díez, Jorge, et al.. (2024). Application of machine learning techniques to predict biodiesel iodine value. Energy. 292. 130638–130638. 11 indexed citations

Díez, Jorge, et al.. (2024). Prediction of the cold flow properties of biodiesel using the FAME distribution and Machine learning techniques. Journal of Molecular Liquids. 400. 124555–124555. 13 indexed citations

Díez, Jorge, et al.. (2023). Users' photos of items can reveal their tastes in a recommender system. Information Sciences. 642. 119227–119227. 4 indexed citations

Díez, Jorge, et al.. (2023). All-in-one picture: visual summary of items in a recommender system. Neural Computing and Applications. 35(27). 20339–20349.

Díez, Jorge, et al.. (2020). Towards explainable personalized recommendations by learning from users’ photos. Information Sciences. 520. 416–430. 22 indexed citations

10.

Díaz, Iñaki, José Catalán, Francisco J. Badesa, et al.. (2018). Development of a robotic device for post-stroke home tele-rehabilitation. Advances in Mechanical Engineering. 10(1). 32 indexed citations

11.

González, Pablo, Jorge Díez, Nitesh V. Chawla, & Juan José del Coz. (2016). Why is quantification an interesting learning problem?. Progress in Artificial Intelligence. 6(1). 53–58. 18 indexed citations

12.

Polo, David, et al.. (2014). Viral elimination during commercial depuration of shellfish. Food Control. 43. 206–212. 42 indexed citations

13.

Piles, Miriam, Jorge Díez, Juan José del Coz, et al.. (2013). Predicting fertility from seminal traits: Performance of several parametric and non-parametric procedures. Livestock Science. 155(1). 137–147. 9 indexed citations

14.

Luaces, Oscar, Jorge Díez, José Barranquero Tolosa, Juan José del Coz, & Antonio Bahamonde. (2012). Binary relevance efficacy for multilabel classification. Progress in Artificial Intelligence. 1(4). 303–313. 152 indexed citations

15.

Tolosa, José Barranquero, Pablo González, Jorge Díez, & Juan José del Coz Díaz. (2012). On the study of nearest neighbor algorithms for prevalence estimation in binary problems. Pattern Recognition. 46(2). 472–482. 25 indexed citations

16.

Luaces, Oscar, José Ramón Quevedo, Miguel Pérez‐Enciso, et al.. (2010). Explaining the Genetic Basis of Complex Quantitative Traits through Prediction Models. Journal of Computational Biology. 17(12). 1711–1723. 1 indexed citations

17.

Coz, Juan José del, Jorge Díez, & Antonio Bahamonde. (2009). Learning Nondeterministic Classifiers. Journal of Machine Learning Research. 10(79). 2273–2293. 42 indexed citations

18.

Lorca, Pedro Tedde de, Javier de Andrés Suárez, Jorge Díez, Juan José del Coz, & A. Bahamonde. (2007). El análisis de preferencias: un nuevo enfoque para el estudio de la rentabilidad empresarial. Investigación Económica. 31(2). 221–264.

19.

Díez, Jorge, P. Albertı́, G. Ripoll, et al.. (2006). Using machine learning procedures to ascertain the influence of beef carcass profiles on carcass conformation scores. Meat Science. 73(1). 109–115. 25 indexed citations

20.

Coz, Juan José del, Gustavo F. Bayón, Jorge Díez, et al.. (2004). Trait Selection for Assessing Beef Meat Quality Using Non-linear SVM. Neural Information Processing Systems. 17. 321–328. 13 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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