I am a Full Professor in the Dept. of Applied Mathematics at the School of Aerospace Engineering of the Universidad Politécnica de Madrid. My research focuses on computational fluid dynamics (CFD), with special emphasis on data-driven methods for identifying and understanding complex spatio-temporal flow patterns.

My work combines reduced-order modelling (ROM), machine learning, deep learning, artificial intelligence (AI) and advanced data analysis techniques to address challenging problems in transitional and turbulent flows, flow control, global stability analysis, and temporal prediction.

I am the founder and leader of ModelFLOWs, an interdisciplinary research group developing CFD-based technologies for cleaner air and combustion systems, improved aerodynamic performance, and personalised medicine applications, while advancing next-generation modelling, data-driven fluid mechanics, and scientific machine learning. Visit our website to discover our projects, tools, publications, and collaborations.