Hybrid Methodology Based on Bayesian Optimization and GA-PARSIMONY for Searching Parsimony Models by Combining Hyperparameter Optimization and Feature Selection. - Francisco Javier Martínez de Pisón; Ruben Gonzalez-Sendino; Alvaro Aldama; Javier Ferreiro-Cabello; Esteban Fraile-Garcia (HAIS, 2017)

GAparsimony: An R Package for Searching Parsimonious Models by Combining Hyperparameter Optimization and Feature Selection. - Francisco Javier Martínez de Pisón; Ruben Gonzalez-Sendino; Javier Ferreiro-Cabello; Esteban Fraile-Garcia; Alpha V. Pernía-Espinoza (HAIS, 2018)

Hybrid methodology based on Bayesian optimization and GA-PARSIMONY to search for parsimony models by combining hyperparameter optimization and feature selection. - F. Javier Martínez-de-Pisón-Ascacibar; Ruben Gonzalez-Sendino; Alvaro Aldama; Javier Ferreiro-Cabello; Esteban Fraile-Garcia (Neurocomputing, 2019)

Mitigating bias in artificial intelligence: Fair data generation via causal models for transparent and explainable decision-making. - Ruben Gonzalez-Sendino; Emilio Serrano; Javier Bajo (Future Gener. Comput. Syst., 2024)

A Review of Bias and Fairness in Artificial Intelligence. - Ruben Gonzalez-Sendino; Emilio Serrano; Javier Bajo; Paulo Novais (Int. J. Interact. Multim. Artif. Intell., 2024)

Quantifying algorithmic discrimination: A two-dimensional approach to fairness in artificial intelligence. - Ruben Gonzalez-Sendino; Emilio Serrano; Javier Bajo (Eng. Appl. Artif. Intell., 2025)

What we learned while automating bias detection in AI hiring systems for compliance with NYC Local Law 144. - Gemma Galdon Clavell; Ruben Gonzalez-Sendino (CoRR, 2025)

Demographic Benchmarking: Bridging Socio-Technical Gaps in Bias Detection. - Gemma Galdon Clavell; Ruben Gonzalez-Sendino; Paola Vazquez (CoRR, 2025)