Implementation of a Reference Architecture for Cyber Physical Systems to support Condition Based Maintenance. - Felix Larrinaga; Javier Fernandez-Anakabe; Ekhi Zugasti; Iñaki Garitano; Urko Zurutuza; Mikel Anasagasti; Mikel Mondragon (CoDIT, 2018)

Null is Not Always Empty: Monitoring the Null Space for Field-Level Anomaly Detection in Industrial IoT Environments. - Ekhi Zugasti; Mikel Iturbe; Iñaki Garitano; Urko Zurutuza (GIoTS, 2018)

An Attribute Oriented Induction based Methodology for Data Driven Predictive Maintenance. - Javier Fernandez-Anakabe; Ekhi Zugasti Uriguen; Urko Zurutuza Ortega (CoRR, 2019)

A Big Data implementation of the MANTIS reference architecture for predictive maintenance. - Felix Larrinaga; Javier Fernandez-Anakabe; Ekhi Zugasti; Iñaki Garitano; Urko Zurutuza; Jon Olaizola; Mikel Anasagasti; Mikel Mondragon (J. Syst. Control. Eng., 2019)

Contrastive Explanations for a Deep Learning Model on Time-Series Data. - Jokin Labaien; Ekhi Zugasti; Xabier De Carlos (DaWaK, 2020)

Interpreting Remaining Useful Life estimations combining Explainable Artificial Intelligence and domain knowledge in industrial machinery. - Oscar Serradilla; Ekhi Zugasti; Carlos Cernuda; Andoitz Aranburu; Julian Ramirez de Okariz; Urko Zurutuza (FUZZ-IEEE, 2020)

Deep learning models for predictive maintenance: a survey, comparison, challenges and prospect. - Oscar Serradilla; Ekhi Zugasti; Urko Zurutuza (CoRR, 2020)

DA-DGCEx: Ensuring Validity of Deep Guided Counterfactual Explanations With Distribution-Aware Autoencoder Loss. - Jokin Labaien; Ekhi Zugasti; Xabier De Carlos (CoRR, 2021)

Deep learning models for predictive maintenance: a survey, comparison, challenges and prospects. - Oscar Serradilla; Ekhi Zugasti; Jon Rodriguez; Urko Zurutuza (Appl. Intell., 2022)

Methodology for data-driven predictive maintenance models design, development and implementation on manufacturing guided by domain knowledge. - Oscar Serradilla; Ekhi Zugasti; Julian Ramirez de Okariz; Jon Rodriguez; Urko Zurutuza (Int. J. Comput. Integr. Manuf., 2022)

Towards Robust Defect Detection in Casting Using Contrastive Learning. - Eneko Intxausti; Ekhi Zugasti; Carlos Cernuda; Ane Miren Leibar; Estibaliz Elizondo (CIARP, 2023)

Diagnostic spatio-temporal transformer with faithful encoding. - Jokin Labaien; Tsuyoshi Idé; Pin-Yu Chen; Ekhi Zugasti; Xabier De Carlos (Knowl. Based Syst., 2023)

Towards a Probabilistic Fusion Approach for Robust Battery Prognostics. - Jokin Alcibar; Jose Ignacio Aizpurua; Ekhi Zugasti (CoRR, 2024)

Navigating the Learning Landscape: A Case Study of Multisubject Problem-Based Learning in Computer Engineering Degree. - Urtzi Markiegi; Alain Perez; Xabier Valencia; Felix Larrinaga; Iñigo Aldalur; Ekhi Zugasti (CSEDU (2), 2025)

A hybrid probabilistic battery health management approach for robust inspection drone operations. - Jokin Alcibar; Jose Ignacio Aizpurua; Ekhi Zugasti; Oier Penagarikano (Eng. Appl. Artif. Intell., 2025)