About

I am an Italian PhD fellow in Mathematics at the University of Ferrara, mostly interested in Many-Valued Multi-Modal Logics and their application to Symbolic Machine Learning. I am also part of the Applied Computational Logic and Artificial Intelligence Lab at the University of Ferrara.

The main goal of my research is to improve Symbolic Machine Learning algorithms through the use (and relative study) of non-classical logic, with a double aim:

• managing to better treat uncertainties and intricate relations in the data
• enhancing Interpretable AI systems performance so that one does not have to give up model interpretation to get accurate outputs

In the last two years I manly focused on the study of Many-Valued Multi-Modal Logics and their algebraic counterpart, contributing to the development of a reasoning tool based on the analytic tableaux technique to check for satisfiability and vadility of formulae in these logics (actually, a many-valued relaxation of these problems).

I am also a Computer Scientist, so (almost) all of my work is (or will be) implemented as well. In the last years, I became very fond of the Julia programming language, and I have been contributing to the development of the Sole.jl ecosystem, a framework for symbolic, transparent, and interpretable machine learning. Specifically, my main contributions have been on the Many-Valued Logic support of SoleLogics.jl, a Julia package for computational logic providing easy manipulation of propositional and (multi-)modal logics, logical formulas and interpretations, as well as algorithms for finite model checking, and on the development of SoleReasoners.jl, a Julia package providing a sat solver and an automatic theorem prover based on analytic tableau technique for Propositional, (Multi-)Modal, Many-Valued, and Many-Valued (Multi-)Modal Logics.

If any of these topics tickles your mind, please send me an e-mail!