bio

I am a CNRS researcher based at the Centre for Data Science at the École Normale Supérieure in Paris working on the crossroads between machine learning and statistical mechanics. I also hold an Adjunct professor (“Professeur Attaché”) position at the Université Paris Sciences et Lettres (PSL) where I teach at the undergraduate and graduate programs of the affiliated universities.

Before moving to CNRS & ENS, I was a postdoc at the Institut de Physique Théorique (IPhT) in Paris and at the École Polytechnique Fédérale de Lausanne (EPFL) in Lausanne, where I worked with Lenka Zdeborová and Florent Krzakala.

Before my postdoc, I read the part III of the Mathematics Tripos at the University of Cambridge, and continued into a PhD at the TCM group in the same university. During my PhD I worked on the Holographic Principle, a duality stemming from string theory that relates quantum field theories to classical theories of gravity. My thesis was centred on applications of this duality to strongly coupled condensed matter systems, with a particular focus on disordered systems.

Although all of that sounds very different from my current research, it is funny to note that many of the methods I employed at the time are the same as in my current topic. In the end, Physics is all about Gaussian integrals, isn’t it?

Want to know more? Check my updated CV.