I have been working as both a research scientist and a cryptography software engineer in the field of homomorphic encryption since 2019.

I am the co-author and principal contributor of Lattigo, a Go library implementing Ring Learning With Errors (RLWE)-based homomorphic encryption (HE) primitives and multiparty homomorphic encryption (MHE) protocols. Lattigo is one of the most widely used open-source libraries for HE and MHE, with over 1.4k stars on GitHub.

Since 2024 I started a new project: Poulpy, the first FHE library to adopt bivariate polynomials to represent Torus poynomials. This Rust library is built from the ground up to be backend agnostic, allowing users to design FHE circuits and implement lattice-based cryptography in a way that is fully generic over the hardware backend.

As a research scientist, I regularly publish in conferences and journals such as PoPETS, Eurocrypt, ACNS, Patterns, and WAHC, and I serve as a reviewer or sub-reviewer for several venues. I have also been multiple times part of the winning teams of the homomorphic encryption track of the iDASH Privacy and Security Workshop challenge.

As an engineer, my industry work focused on researching, designing, implementing, and integrating privacy-preserving machine learning and statistical analytics into large-scale B2B applications. The solutions I developed combined applied cryptography with other privacy-enhancing technologies, including lattice-based fully homomorphic encryption, multiparty computation, federated learning, and differential privacy. In early 2024, I transitioned back to applied research, focusing on developing solutions with homomorphic encryption at their core, now primarily in Rust.

At Phantom Zone, our current project is the design and development of a fully encrypted RISC-V32 virtual machine, as well as an FHE backend (Poulpy) with at its core the hardware acceleration layer of spqlios-arithmetic.