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.
👥 I am co-chairing with Lisa Nguyen Quang Do the 10th International Workshop on the State of the Art in Program Analysis (SOAP 2021)! The deadline for paper submissions is on March 22nd!
👥 I am co-organizing with Jean-Baptiste Jeannin and Arjun Radhakrishna and Suguman Bansal the 7th Verification Mentoring Workshop (VMW 2021)!
👥 I am a member of the SBLP 2021 program committee.
👥 I am a member of the POPL 2022 program committee.
👥 I am co-chairing the SPLASH 2021 Student Research Competition at SPLASH 2021!
👥 I am co-chairing with Marijana Lazić the 7th Logic Mentoring Workshop at FLOC 2022!
👩🏼💻 I have been developing a Python interface for the APRON numerical abstract domain library. Contributions are welcome!
PhD in Computer Science, 2015
École Normale Supérieure, Paris, France
MSc in Computer Science, 2011
Università degli Studi di Udine, Udine, Italy
BSc in Computer Science, 2009
Università degli Studi di Udine, Udine, Italy
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 goal of the Libra project is to develop new analyses and tools to reason about and certify fairness of decision-making software.
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.
Abstract Interpretation and Applications Beyond the Beaten Track
PhD, Doctoral Program in Computer Science, Gran Sasso Science Institute (GSSI), Italy
Abstract Interpretation: Application to Verification and Static Analysis
M2, Master Parisien de Recherche en Informatique (MPRI), Université de Paris, France
Python Interface for the APRON Numerical Abstract Domain Library
Abstract Interpretation-based Static Analysis for (Conditional) Termination (and Other CTL Properties)
Perfectly Parallel Abstract Interpretation-based Fairness Certification for Neural Networks
Abstract Interpretation-based Static Analysis for Data Science Applications