About me

I am a Research Scientist at DeepMind Paris, where I work on scalable machine learning.

Previously I worked as a PostDoc in Lorenzo Rosasco’s Laboratory for Computational and Statistical Learning. Before that I received my PhD in 2017 from INRIA Lille under the supervision of Michal Valko and Alessandro Lazaric working on scalable sequential learning, and even before my Master with Marcello Restelli's group at Politecnico di Milano working on safety and efficiency in reinforcement learning.

My research focuses on adaptive dimensionality reduction techniques using randomized subsampling and sketching. These techniques have been successfully applied (2014-2018)  to optimization of noisy function, learning on graphs, clustering and supervised regression. My recent interest (2018-present) is to transfer some of these adaptive randomization techniques to bandit/bayesian optimization, experimental design and reinforcement learning.