Towards Explaining the Effects of Data Preprocessing on Machine Learning. - Carlos Vladimiro Gonzalez Zelaya (ICDE, 2019)

Fair-MDAV: An Algorithm for Fair Privacy by Microaggregation. - Julián Salas; Vladimiro González-Zelaya (MDAI, 2020)

Technologies for Trustworthy Machine Learning: A Survey in a Socio-Technical Context. - Ehsan Toreini; Mhairi Aitken; Kovila P. L. Coopamootoo; Karen Elliott; Vladimiro González-Zelaya; Paolo Missier; Magdalene Ng; Aad van Moorsel (CoRR, 2020)

Optimising Fairness Through Parametrised Data Sampling. - Vladimiro González-Zelaya; Julián Salas; Dennis Prangle; Paolo Missier (EDBT, 2021)

Preprocessing Matters: Automated Pipeline Selection for Fair Classification. - Vladimiro González-Zelaya; Julián Salas; Dennis Prangle; Paolo Missier (MDAI, 2023)

Differentially Private Graph Publishing Through Noise-Graph Addition. - Julián Salas; Vladimiro González-Zelaya; Vicenç Torra; David Megías 001 (MDAI, 2023)

Fair and Private Data Preprocessing through Microaggregation. - Vladimiro González-Zelaya; Julián Salas; David Megías 001; Paolo Missier (ACM Trans. Knowl. Discov. Data, 2024)

Fairness in Student Allocation and Group Formation. - Matthew Forshaw; Cristina Adriana Alexadru; Caitlin Bentley; Vladimiro González-Zelaya; Joseph Kwame Adjei; Vangel V. Ajanovski; Mireilla Bikanga Ada; Julian Brooks; Joshua Burridge; Alex Chao; Rutwa Engineer; Olga Glebova; et al. (ITiCSE (2), 2025)