Luca Muscarà

Luca Muscarà is an Application Engineer with a PhD in Aerospace Engineering (2025), obtained through a joint program between Politecnico di Torino and Optimad–ESTECO. His research focused on data-driven methods and machine learning applications in Computational Fluid Dynamics (CFD), with the goal of improving turbulence modeling. In particular, his work explored the integration of machine learning and field inversion techniques to enhance the predictive capabilities of Reynolds-Averaged Navier–Stokes (RANS) models, especially in challenging scenarios such as flow separation and transition. This involved implementing data-driven frameworks, adjoint-based optimization techniques, and neural network models.

Currently, he works as an Application Engineer at ESTECO, where he bridges research and industrial applications by working on real-world CFD problems, optimization tasks, and the development of surrogate models and reduced-order modeling (ROM) techniques. His work focuses on speeding up simulation-driven design by reducing computational cost while maintaining accuracy.