Ricerc@Sapienza

I am an associate professor at Sapienza University of Rome. My research interests include the design of efficient and explainable neural network models, topological and geometric deep learning, and continual learning, as well as their applications to scientific discovery, intelligent telecommunications, medicine, and environmental monitoring.

I teach Neural Networks for Data Science Applications in the M.Sc. in Data Science, co-teach Neural Networks in the M.Sc. in AI and Robotics and the M.Sc. in Computer Engineering, and Fundamental of Machine Learning in the B.Sc. in Telecommunication Engineering. I have also held PhD courses on reproducibility, explainability, and continual learning. Recently, I wrote a book on the design of neural networks.

I am an affiliate researcher at the National Institute for Nuclear Physics (INFN), a junior fellow at the Sapienza School for Advanced Studies, and a member of the National Inter-University Consortium for Telecommunications (CNIT) and the ELLIS society. I am involved in several national and European projects, as the PI of two active Sapienza grants (DESMOS and CENTS), co-PI of MUCCA (Chist-ERA project on explainable AI for scientific discovery), task leader in 6G-GOALS (SNS-JU project on goal-oriented communications) and WP leader in RELAY (a project on relational deep learning for energy management funded by the Research Council of Norway).

Between 2017 and 2021, I was involved in several no-profit machine learning activities: I co-founded and chaired the Italian Association for Machine Learning (now closed), co-organized the Rome Machine Learning & Data Science Meetup, and co-hosted the Smarter Podcast. I was also a machine learning Google Developer Expert.