I am an Assistant Professor (Maître de Conférences) in the Data Science Department at EURECOM. My research focuses on probabilistic machine learning, with particular emphasis on Bayesian inference, scalable approximate methods, and the theoretical foundations of deep learning.
I’m always looking for interns and PhD students to join my team. If you’re interested in uncertainty quantification, probabilistic reasoning, or scalable Bayesian methods, please reach out.
About me
Engineer turned machine learning researcher with a focus on probabilistic modeling and scalable inference.
I study Bayesian methods for deep learning, including variational inference, Gaussian processes, and uncertainty quantification. My work has been published at ICML, AISTATS, NeurIPS, and JMLR, I have given tutorials and talks at IJCAI and I actively contribute to academic peer review and collaborative research.
Before joining EURECOM, I worked at Stellantis on AI for autonomous systems and completed a Ph.D. in Computer Science at Sorbonne Université. My background spans electronic and computer engineering, with degrees from Politecnico di Torino and Telecom ParisTech.
- Ph.D. ∙ Sorbonne Université ∙ 2022
- M.Sc. ∙ Politecnico di Torino ∙ 2018
- M.Sc. ∙ Telecom ParisTech ∙ 2018
- B.Sc. ∙ University of Genova ∙ 2015