I am a PhD Student in a joint program between the Artificial and Mechanical Intelligence research lab and the Theoretical and Applied Aerodynamic Research Group at Università degli Studi di Napoli Federico II. My PhD research focuses on developing methodologies to model and control aerodynamic forces acting on flying humanoid robots via CFD simulations, machine learning models, and momentum-based whole-body flight controllers. I did my PhD secondment at the Mechanical Engineering Department of Stanford University as a Visiting Student, collaborating to develop machine learning models to predict the aerodynamic flow over the surface of the iRonCub robot. I'm enrolled in the PhD program from November 2022 to October 2025.
As a research fellow, I have been part of the iRonCub team at the Artificial and Mechanical Intelligence research line from September 2021 to October 2022, contributing to the enhancement of CFD simulations and validation through wind tunnel tests on the iRonCub-Mk1 robotic platform.
I received my MSc degree in Aerospace Engineering in 2021 with the highest honors from Università degli Studi di Napoli Federico II, with the thesis titled "Computational Fluid Dynamics study on Aerial Humanoid Robotics: Aerodynamic analysis of iRonCub robot in flight" concerning the study of the aerodynamics effects on a flying humanoid robot through CFD simulations. The thesis work has been carried on at the Artificial and Mechanical Intelligence research lab since December 2020.
I received the BSc degree in Aerospace Engineering in 2018 at the Università degli Studi di Napoli Federico II, with the thesis titled "TOMO-PIV analysis of circular and chevron impinging jets" at the Laboratory of Gasdynamics.
My research interests include the estimation and control of aerodynamic effects on aerial robots, using data-driven methodologies for effective modeling. I recently started applying machine learning and deep learning methods to predict turbulent aerodynamic flows around 3D bodies.
