Salvador García
Also known as Salvador García López
Salvador García is a computer scientist at the University of Granada whose research covers data preprocessing, imbalanced learning and the statistical comparison of learning algorithms. He earned his computer science degree in 2004 and his doctorate in 2008 at Granada, and from 2008 to 2015 he worked in the Department of Computer Science at the University of Jaén. In 2008 he and Francisco Herrera published a JMLR paper on statistical comparisons of classifiers, and in 2014 he co-authored the Springer book Data Preprocessing in Data Mining. Clarivate named him a Highly Cited Researcher every year from 2014 to 2020, and he co-authored a 2018 review of SMOTE in the Journal of Artificial Intelligence Research and a 2019 overview of explainable AI. As of October 2026, he is a Catedrático de Universidad in Granada's Department of Computer Science and Artificial Intelligence and Research Coordinator for data science and big data at DaSCI.
- Now at
- Universidad de Granada and Andalusian Research Institute in Data Science and Computational Intelligence
- Works
- 277
- Citations
- 45,154
- h-index
- 64
- Badges
Publication numbers from OpenAlex, as of 22 October 2026.
Timeline
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2004–2008
Degrees at the University of Granada
He earns his computer science degree in 2004 and his doctorate in 2008, both at the University of Granada.
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2008
Comparing classifiers statistically
In 2008, he and Francisco Herrera publish “An Extension on ‘Statistical Comparisons of Classifiers over Multiple Data Sets’ for all Pairwise Comparisons” in JMLR. The paper builds on Demšar's 2006 recommendations and proposes more powerful procedures for comparing n × n classifiers.
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2008–2015
Faculty at the University of Jaén
From 2008 to 2015, he is a Titular de Universidad in the Department of Computer Science at the University of Jaén. In 2011, his research there covers data mining, data reduction, data complexity, imbalanced learning, statistical inference and evolutionary algorithms.
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2014
Data Preprocessing in Data Mining
With Julián Luengo and Francisco Herrera, he co-authors the book Data Preprocessing in Data Mining, which Springer publishes in September 2014.
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2014–2020
Clarivate Highly Cited Researcher
Clarivate names him a Highly Cited Researcher in each year from 2014 to 2020. In 2017, he is one of four University of Granada researchers on the list, among the global top 150 authors in computer science.
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2018
SMOTE after fifteen years
In 2018, he co-authors a Journal of Artificial Intelligence Research review of SMOTE, the oversampling technique for imbalanced data, with Alberto Fernández, Francisco Herrera and Nitesh V. Chawla. The paper marks the fifteenth anniversary of SMOTE and names the challenges of extending it to Big Data.
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2019
A survey of explainable AI
In October 2019, he is one of twelve authors, with Alejandro Barredo Arrieta first and Francisco Herrera last, of an arXiv overview of explainable artificial intelligence. The paper builds a taxonomy of explainability for machine learning and deep learning models and arrives at the concept of Responsible AI.
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As of October 2026
Catedrático at the University of Granada
He is a Catedrático de Universidad in the Department of Computer Science and Artificial Intelligence at the University of Granada, where he belongs to the SCI2S research group. At DaSCI, the Andalusian Research Institute in Data Science and Computational Intelligence, he is Research Coordinator for data science and big data.
Career
- Since 2006Universidad de GranadaCatedrático de Universidad
- NowAndalusian Research Institute in Data Science and Computational IntelligenceResearch Coordinator for data science and big data
- 2015–2017King Abdulaziz University
- 2008–2015Universidad de JaénTitular de Universidad
Education
- 2008Universidad de GranadaDoctorate
- 2004Universidad de GranadaComputer science degree
Most-cited works
- Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AIWith Francisco Herrera and Raja Chatila
- A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithmsWith Francisco Herrera
- KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis FrameworkWith Francisco Herrera
- Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of powerWith Francisco Herrera
- SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year AnniversaryWith Francisco Herrera and Nitesh Chawla
Sources and credits
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- Salvador García López – DaSCI
- Salvador García — Thirteenth International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC-2011) — HSE University
- An Extension on “Statistical Comparisons of Classifiers over Multiple Data Sets” for all Pairwise Comparisons
- SALVADOR GARCÍA LÓPEZ - Universidad de Jaén
- Data Preprocessing in Data Mining - Salvador García, Julián Luengo, Francisco Herrera - Google Books
- Four UGR researchers among the most highly cited in the world
- SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary | Journal of Artificial Intelligence Research
- [1910.10045] Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI
- Salvador García López | Universidad de Granada
- SALVADOR GARCÍA LÓPEZ - Universidad de Granada


