Diana Carrera is a seasoned Risk Modeler at DeNexus since November 2022, with extensive experience in machine learning research. Prior to their current role, Diana served as a Machine Learning Researcher at UPV/EHU from 2016 to November 2022, where innovative approaches to supervised classification and graphical structure learning were developed using vine-copula models. Diana's earlier experience at the Institute of Cybernetics, Mathematics and Physics (ICIMAF) from 2012 to 2017 involved the design of evolutionary algorithms and the development of techniques for texture image recognition. Diana holds a PhD in Informatics Engineering from Universidad del País Vasco and both an MSc in Mathematics and a BS in Computer Science from the University of Havana.