My research career has always revolved around Statistical Physics, inference problems and machine learning. My area of expertise is interdisciplinary: a strong part of my research is linked to disordered systems and its statistical properties. While the other part tries to understand inference and learning phenomenon through the prism of the physics of disordered systems.
After my PhD in 2011, I have been hired as postdoc at the university of Rome for 3 years and later I have been recruited as an associate professor at university Paris Saclay. I’m now a postdoc from the "Atracción de Talento" program of Madrid at the UCM since July 2020 (on leave of absence of Paris-Saclay).

My research interests are now focused on the following thematic

• Understanding Machine Learning through the prism of Statistical mechanics. In particular, I'm studying the Restricted Boltzmann Machine, its learning behavior as well as the evaluation of the learned machine
• Applying Machine Learning methods to: biology - generation of artificial genome or learning features on families of proteins, for instance
• Developing statistical method applied to Cosmology