Research and development in symbolic AI, applied category theory, compilers and programming languages. Building the core infrastracture, working on interdisciplinary problems since the early stages of the company. Contributing to UI and infrastructure. We’re building an AI system which accurately represents knowledge and uncertainty, to enable the discovery of insights and transparent problem solving.

During GSoC 2024, I mentored Niklas Heim’s project OptiFloat.jl. Based on my project Metatheory.jl, OptiFloat.jl rewrites floating point expressions to more accurate alternatives. It is a pure Julia implementation of Herbie. To learn more about what OptiFloat does, how to use it, and how it works check out the documentation.

I completed my undergraduate studies in Computer Science at the University of Pisa. My thesis proposes an advanced, generic and high-level code rewriting and analysis system for the Julia programming language, and was supervised by Professors Gian-Luigi Ferrari, Andrea Corradini and Dr. Christopher Rackauckas

During GSoC 2021, I was awarded a stipend from Google for an experiment involving the integration of Metatheory.jl, my thesis project, with the high performance Computer Algebra System (CAS) Symbolics.jl developed at MIT. The project focused on automatically applying user-defined high-level compiler optimizations, defined via equational rewrite rules, to preemptively choose the symbolic representation of a system of differential equations that performs best when compiled and solved numerically. The projects are still being maintained and there is still room for exploring and researching the topic.

High school sponsored internship, focused on the development of full stack backoffice applications in Node.js and React.

Short intership, sponsored by the Erasmus program for high school students. I focused on development of various visual detection systems for embedded computers with OpenCV running on Raspberry Pis, and a mobile application in React Native.