WALLEZ Théophile

PhD Student


theophile.wallez [at] inria.fr

Short bio

Master of Computer Science, ENS Ulm

Research project

A verification framework for privacy-preserving machine learning.

Short abstract

Machine learning is known to be hungry for data, which is often private. Recent advances in privacy-preserving machine learning use new cryptographic techniques to avoid exposing private data. However, such cryptographic implementations are error-prone, resulting in information leakage. Therefore, I use the F* software verifier to implement modern multiparty computation protocols, such as SPDZ2k.