About me

I am a researcher at Université Libre de Bruxelles, pursuing a PhD co-supervised by RWTH Aachen University. My fellowship is part of the Horizon Europe MSCA program, which funds the ENCODING project. Since my master’s studies, I have specialized in computational fluid dynamics, combustion, and machine learning.

Research

My current research interests are turbulent combustion modeling and deep learning. The goal of my PhD is to train neural networks on high-fidelity data to gain insights into turbulence-chemistry interaction. The main challenge of the approach is the model generalizability, that I am trying to improve focusing on Bayesian techniques to quantify uncertainty in neural networks. Our latest research proposes a hybrid data-driven/physics-based framework to model the chemical source terms in Large Eddy Simulations.

Previous

I studied Aerospace Engineering at Politecnico di Torino, with a thesis on multiphase heat exchangers at the Von Karman Institute for Fluid Dynamics. During my Master’s, I joined for two years H2politO, a students’ team that designs sustainable vehicle prototypes.