Researcher and PhD in the field of artificial intelligence. She began her studies in Mechanical Engineering at the University of La Rioja in 2011 and completed them in 2015. She then furthered her education with a Master's degree in Industrial Engineering at the same University of La Rioja, which she completed with her master's thesis dedicated to predicting phosphorus concentration in steel production using machine learning techniques in 2017. In 2023, she defended her doctoral thesis at the University of the Basque Country (UPV/EHU) on the context and application of advanced Machine Learning techniques for predictive maintenance. Her research focuses on pattern analysis and anomaly detection to predict failures in industrial machinery. She works at Tecnalia in the Artificial Intelligence platform/area of the Digital Unit, and her main research interests are advanced data analysis models for anomaly detection in industrial time series, metaheuristic and hyper-heuristic optimization, classification methods, clustering, Explainable AI (XAI), and building trustworthy models.