Research, innovation and knowledge transfer in rotating machinery, reliability, diagnostics and prognostics.
Research starts with real machinery problems: recognizing deviations, understanding their mechanisms and estimating how they evolve.
His approach combines condition monitoring, domain knowledge, statistics, machine learning and deep learning. The quality of an alert depends on its connection to operating context and its usefulness to the specialist who must act.
Research and knowledge-transfer connection in industrial reliability, data analytics and RAMS studies. Ernesto’s participation is listed on UNED’s official innovation website. Research into prognostics and analytics and artificial intelligence applications.
Final degree project on mixed reliability calculations for rotating machinery applied to a wind turbine. Used CReW turbine data to investigate and compare different reliability calculation models.
Doctoral research completed in 2026, focused on distinguishing normal and anomalous rotating machinery behavior, evaluating models and turning analytical results into useful operational decisions.
Instituto Universitario de Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería. The SIANI name appears in the supplied logo and the 2024 Machines article affiliation.
Collaboration as a rotating machinery specialist in offshore wind research. The European project develops technologies and tools to reduce costs across the wind farm lifecycle and supply chain.
