I hold a Ph.D. in Robotics Engineering from the University of Genoa, as well as an M.Sc. in Robotics Engineering from the University of Genoa and an M.Sc. in Automatique, Robotics, Signals et Images from École Centrale de Nantes. My academic background has provided me with a strong foundation in robotics, control theory, signal processing, and applied mathematics, with a particular emphasis on the integration of modeling and computation.

My research focuses on robotics and autonomous systems, with a specific interest in data-driven control and physics-informed machine learning. I investigate how learning-based models can be constrained and guided by physical laws to improve robustness, interpretability, and generalization, especially in safety-critical and resource-constrained scenarios.

A significant part of my work is devoted to embedded and edge computing for robotics and remote sensing, where I explore lightweight learning architectures and distributed intelligence. I am particularly interested in bridging the gap between high-level learning algorithms and low-level embedded implementations, enabling adaptive and efficient robotic systems that operate reliably in real-world environments.