Hello! I am Miguel Alfonso Mendez. Since October 1st, 2026, my primary affiliation is the SAAS (Service d'Automatique et d'Analyse des Systèmes) Department at the Brussels School of Engineering, Université libre de Bruxelles (ULB; the department website is currently being updated). I am also Associate Professor at the von Karman Institute for Fluid Dynamics (VKI) and affiliated with the Department of Aerospace Engineering at Universidad Carlos III de Madrid (UC3M).

I lead the ML4F — Machine Learning for Fluid Systems group, which spans the three affiliations (SAAS–ULB, VKI and UC3M) and focuses on the development of hybrid physics–data methodologies for modeling, identification, and control of complex fluid and thermo-fluid systems. Core activities include data assimilation and digital twinning, reduced-order modeling, physics-informed and physics-constrained learning, and learning-based control, with strong links to experiments and real-time applications.

At ULB, I teach signal processing and data-driven engineering. At VKI, within the Institute’s postgraduate Research Master (Master-after-Master), I teach differential equations, signal processing, experimental methods, and machine learning applied to fluid dynamics. At UC3M, I give yearly mini-courses in the Doctoral Program on data assimilation, digital twinning, and control.

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