I am looking for for strong and motivated postdocs and PhD students to work on a collaborative project with Fujitsu Japan on practical formal verification methods for machine learning. The start date is any time, but the sooner the better. Contact me if interested!
I am a member of the INRIA research team ANTIQUE (ANalise StaTIQUE). Previously, I was a postdoctoral researcher at the Chair of Programming Methodology, led by Peter Müller at ETH Zurich. I completed my Ph.D. in Computer Science, working under the joint supervision of Radhia Cousot and Antoine Miné at École Normale Supérieure.
I hold a Bachelor’s and a Master’s degree in Computer Science, both received with full marks and honors (summa cum laude) from the Università degli Studi di Udine.
My research interests span the whole spectrum of formal methods and aim at developing methods and tools to enhance the reliability of computer software and understanding complex software systems. My main area of expertise is static analysis based on abstract interpretation, which provides rigorous mathematical guarantees of the behavior of computer programs. I am currently engaged in a long-term research effort to enhance the understanding and reliability of data science software, which nowadays plays an increasingly important role in critical decision making in fields such as finance and medicine.
The goal of the FuncTion project was the development of a static analyzer which automatically infers ranking functions and sufficient precondition for program termination (and other liveness properties) by means of abstract interpretation.
The Lyra research project is a long-term research effort to enhance the understanding and reliabilty of data science software. It aims ad developing new practical and accessible analyses and tools to reason about and provide rigorous guarantees of the behavior of data analytics, big data, machine learning, and deep learning applications.
