Jose M. Moyano

About

Who Am I?

Hi, I'm Jose M. Moyano. I'm a Ph.D. in Computer Science and post-doctoral researcher at the KDIS Research Group of the University of Córdoba. The thesis, called "Multi-Label Classification Models for Heterogeneous Data: an Ensemble-based Approach", was defended on September 2020. It was developed enrolled in a dual Ph.D. program at both University of Córdoba (Spain) and Virginia Commonwealth University (USA), and supervised by Eva L. Gibaja, Krzysztof J. Cios, and Sebastián Ventura. This research was granted by the Spanish Ministry of Education under FPU Grant FPU15/02948, as well as by projects TIN2017-83445-P and TIN2014-55252-P. Further, I obtained the B.Sc. in Computer Science at University of Córdoba in 2014, and then th M.Sc. degree in the same university in 2016.

So far, I have published nine journal articles (seven of them as first author and Q1 journals), as well as seven papers in international conferences and seven in national conferences.

Finally, I am also assistant professor at University of Córdoba since 2017, and at Menéndez Pelayo International University since course 2019/2020.

GitHub

Google Scholar

Dblp

ResearchGate

Research publications

Journal papers

Jose M. Moyano and Sebastián Ventura. (2022). Auto-adaptive Grammar-Guided Genetic Programming algorithm to build Ensembles of Multi-Label Classifiers. Information Fusion, 78: 1-19. DOI: 10.1016/j.inffus.2021.07.005. Bibtex.

Mario Frias*, Jose M. Moyano*, Antonio Rivero-Juarez, Jose M. Luna, Ángela Camacho, Habib M. Fardoun, Isabel Machuca, Mohamed Al-Twijri, Antonio Rivero, Sebastian Ventura. (2021). Classification Accuracy of Hepatitis C Virus Infection Outcome: Data Mining Approach. Journal of Medical Internet Research, 23(2): e18766. DOI: 10.2196/18766. Bibtex. [*Both authors contributed equally.]

Jose M. Moyano, Oscar Reyes, Habib M. Fardoun, Sebastian Ventura. (2021). Performing multi-target regression via gene expression programming-based ensemble models. Neurocomputing, 432: 275-287. DOI: 10.1016/j.neucom.2020.12.060. Bibtex.

Jose M. Moyano, Eva L. Gibaja, Krzysztof J. Cios, and Sebastián Ventura. (2020). Combining multi-label classifiers based on projections of the output space using Evolutionary algorithms. Knowledge-Based Systems, 196: 105770. DOI: 10.1016/j.knosys.2020.105770. Bibtex.

Jose M. Moyano, Eva L. Gibaja, Krzysztof J. Cios, and Sebastián Ventura. (2019). An Evolutionary approach to build ensembles of multi-label classifiers. Information Fusion, 50: 168-180. DOI: 10.1016/j.inffus.2018.11.013. Bibtex.

Jose M. Moyano, Eva L. Gibaja, Krzysztof J. Cios, and Sebastián Ventura. (2018). Review of ensembles of multi-label classifiers: Models, experimental study and prospects. Information Fusion, 44: 33-45. DOI: 10.1016/j.inffus.2017.12.001. Bibtex.

Isaac Triguero, Sergio González, Jose M. Moyano, Salvador García, Jesús Alcalá-Fdez, Julián Luengo, Alberto Fernández, Maria José del Jesus, Luciano Sánchez, and Francisco Herrera. (2017). KEEL 3.0: An open source software for multi-stage analysis in data mining. International Journal of Computational Intelligence Systems, 10(1): 1238-1249. DOI: 10.2991/ijcis.10.1.82. Bibtex.

Jose M. Moyano, Eva L. Gibaja, and Sebastián Ventura. (2017). MLDA: A tool for analyzing multi-label datasets. Knowledge-Based Systems, 121: 1-3. DOI: 10.1016/j.knosys.2017.01.018. Bibtex.

Eva L. Gibaja, Jose M. Moyano, and Sebastián Ventura. (2016). An ensemble-based approach for multi-view multi-label classification. Progress in Artificial Intelligence, 5(4): 251-259. DOI: 10.1007/s13748-016-0098-9. Bibtex.

International conferences

Jose M. Moyano, Eva L. Gibaja, Krzysztof J. Cios, and Sebastián Ventura. (2020). Tree-shaped ensemble of multi-label classifiers using grammar-guided genetic programming. In 2020 IEEE Congress on Evolutionary Computation, CEC 2020. 1-8. DOI: 10.1109/CEC48606.2020.9185661. Bibtex.

Jose M. Moyano, Eva L. Gibaja, Krzysztof J. Cios, and Sebastián Ventura. (2020). Generating Ensembles of Multi-Label Classifiers Using Cooperative Coevolutionary Algorithms. In 24th European Conference on Artificial Intelligence, ECAI 2020, 1379-1386. DOI: 10.3233/FAIA200242. Bibtex.

Jose M. Moyano, Eva L. Gibaja, Sebastián Ventura, and Alberto Cano. (2019). Speeding Up Classifier Chains in Multi-Label Classification. In 4th International Conference on Internet of Things, Big Data and Security, IoTBDS 2019, 29-37. DOI: 10.5220/0007614200290037. Bibtex.

Oscar Reyes, Jose M. Moyano, Jose M. Luna, and Sebastián Ventura. (2018). A gene expression programming method for multi-target regression. In International Conference on Learning and Optimization Algorithms: Theory and Applications, LOPAL 2018, 2:1-2:6. DOI: 10.1145/3230905.3230910. Bibtex.

Jose M. Moyano, Eva L. Gibaja, and Sebastián Ventura. (2017). An evolutionary algorithm for optimizing the target ordering in ensemble of regressor chains. In 2017 IEEE Congress on Evolutionary Computation, CEC 2017, 2015-2021. DOI: 10.1109/CEC.2017.7969548. Bibtex.

Oliver Sánchez, Jose M. Moyano, Luciano Sánchez, and Jesús Alcalá-Fdez. (2017). Mining association rules in R using the package RKEEL. In 2017 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2017, 1-6. DOI: 10.1109/FUZZ-IEEE.2017.8015572. Bibtex.

Jose M. Moyano and Luciano Sánchez. (2016). RKEEL: Using KEEL in R code. In 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016, 257-264. DOI: 10.1109/FUZZ-IEEE.2016.7737695. Bibtex.

Ph.D. thesis

Jose M. Moyano. (2020). Multi-Label Classification Models for Heterogeneous Data: an Ensemble-based Approach. Ph.D thesis. University of Córdoba (Spain) and Virginia Commonwealth University (USA). Dissertation. Slides. Bibtex.

National conferences

Oscar Reyes, Jose M. Moyano, Antonio Rivero-Juárez, Raúl M. Luque, Antonio Rivero, Justo Castaño, and Sebastián Ventura. (2018). Extracción de factores relevantes en el análisis de datos biomédicos: una metodología basada en técnicas de aprendizaje supervisado. In IX Simposio de Teoría y Aplicaciones de la Minería de Datos, TAMIDA 2018, CAEPIA 2018, 861-866. Available online. Bibtex.

Oscar Reyes, Jose M. Moyano, Jose M. Luna, and Sebastián Ventura. (2018). Resolviendo el problema de regresión multi-salida mediante Gene Expression Programming. In IX Simposio de Teoría y Aplicaciones de la Minería de Datos, TAMIDA 2018, CAEPIA 2018, 907-912. Available online. Bibtex.

Oscar Reyes, Jose M. Luna, Jose M. Moyano, Eduardo Pérez, and Sebastián Ventura. (2018). Resolución de problemas biomédicos mediante técnicas de extracción de conocimiento. In XVIII Conferencia de la Asociación Española para la Inteligencia Artificial, CAEPIA 2018, 1252-1257. Available online. Bibtex.

Jose M. Moyano, Eva L. Gibaja, and Sebastián Ventura. (2016). Una herramienta para analizar conjuntos de datos multi-etiqueta. In XVII Conferencia de la Asociación Española para la Inteligencia Artificial, CAEPIA 2016, 857-866. Available online. Bibtex.

Jose M. Moyano, Eva L. Gibaja, and Sebastián Ventura. (2015). Diseño automático de multi-clasificadores basados en proyecciones de etiquetas. In XVI Conferencia de la Asociación Española para la Inteligencia Artificial, CAEPIA 2015, 355-365. Available online. Bibtex.

Eva L. Gibaja, Jose M. Moyano, and Sebastián Ventura. (2015). Combinación de vistas para clasificación multi-etiqueta: estudio preliminar. In VII Simposio de Teoría y Aplicaciones de la Minería de Datos, TAMIDA 2015, CAEPIA 2015, 759-768. Available online. Bibtex.

Jose M. Moyano, Eva L. Gibaja, Alberto Cano, Jose M. Luna, and Sebastián Ventura. (2015). Algoritmo evolutivo para optimizar ensembles de clasificadores multi-etiqueta. In X Congreso Español de Metaheurísticas, Algoritmos Evolutivos y Bioinspirados, MAEB 2015, 219-225. Available online. Bibtex.

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23 Total research publications

7 Q1 journal papers

288 Total cites

7 H-index

Source: Google Scholar, August 2021

Teaching

3D Computer Graphics

4º B.Sc. in Computer Engineering. University of Córdoba.

Spring 2020. 16 hours.

Spring 2019. 24 hours.

Advanced Software Modeling and Design

3º B.Sc. in Computer Engineering. University of Córdoba.

Spring 2020. 24 hours.

Computer Basics

1º B.Sc. in Mechanical Engineering. University of Córdoba.

Spring 2018. 12 hours.

Intelligent Systems

2º B.Sc. in Computer Engineering. University of Córdoba.

Spring 2021. 24 hours.

Spring 2020. 8 hours.

Spring 2019. 16 hours.

Interactive Systems (Human-Computer Interaction)

3º B.Sc. in Computer Engineering. University of Córdoba.

Spring 2021. 24 hours.

Formal Methods in Software Engineering

4º B.Sc. in Computer Engineering. University of Córdoba.

Spring 2021. 18 hours.

Metaheuristics

3º B.Sc. in Computer Engineering. University of Córdoba.

Spring 2019. 14 hours.

Programming Methodology

1º B.Sc. in Computer Engineering. University of Córdoba.

Spring 2021. 48 hours.

Spring 2020. 12 hours.

Spring 2019. 6 hours.

Software Engineering

2º B.Sc. in Computer Engineering. University of Córdoba.

Fall 2021. 60 hours.

Unsupervised Methods

M.Sc. in Artificial Intelligence. Menéndez Pelayo International University.

Fall 2020 - Spring 2021. Teaching Assistant.

Spring 2020. Teaching Assistant.

Web Programming

3º B.Sc. in Computer Engineering. University of Córdoba.

Spring 2018. 48 hours.

Supervision of Final Degree Projects

A Julia library for genetic algorithms in binary and integer representation, and grammatical evolution.

Manuel Rafael Luque Cuesta.

Grade: 10, with honors.

B.Sc. in Computer Engineering. University of Córdoba. July 2020.

A Julia library for genetic programming: GP, STGP, and GEP.

Sergio Gómez Morales.

Grade: 10, with honors.

B.Sc. in Computer Engineering. University of Córdoba. July 2020.

Education

Ph.D. in Computer Science 2016 - 2020

Dual Ph.D. program at both University of Córdoba (Spain) and Virginia Commonwealth University (USA).

Hired by the University of Córdoba under a competitive FPU Grant from the Spanish Ministry of Education. Member of the KDIS Research Group and participant in national research projects.

The thesis is called "Multi-Label Classification Models for Heterogeneous Data: an Ensemble-based Approach", and it was done under the guidance of Dr. Eva L. Gibaja, Dr. Krzysztof J. Cios, and Dr. Sebastián Ventura as advisors.