I’m a PhD student at the Max Planck Institute for Software Systems (MPI-SWS), in Germany.

I work in the Distributed Systems and Security & Privacy groups, where I am co-advised by Peter Druschel and Deepak Garg. I am broadly interested in designing, building, and analyzing secure and privacy-preserving distributed systems. In particular, I am studying cryptographic techniques that run computation on sensitive private data; my research focus is to apply these techniques to real-world large-scale distributed systems, and to explore the consequent trade-offs between security, efficiency, and functionality.

Recently, I have been working on a secure selective analytics (SSA) platform. This platform is secure under a strong threat model that leverages Multi-Party Computation (MPC) to place trust on a set of independent Trusted Execution Environments. This platform is selective as it allows data sources to a priori restrict the use of their sensitive data to a pre-defined set of queries, run by specific analysts, and for a limited period. Currently, I am working on extending its use cases to support practical MPC-based ML training over very large sensitive datasets under the same threat model.

Previously, I explored different areas such as network side channels and secure mobile systems: I worked on Pacer, a project aimed to ensure data privacy in Cloud services against network side-channel leaks, and enClosure, a project on secure and private communication enabled by chains of mobile encounters.

Besides research, I’m quite enthusiastic about a bunch of things: traveling, cinema, books, comics, guitar, food, complaining, and complaining about food – especially if claimed to be Italian.


  • Security and Privacy
  • Distributed Systems
  • Confidential Computing
  • Applied Cryptography
  • Multi-Party Computation
  • Mobile Systems


  • MSc in Computer Engineering

    Universita' degli Studi di Napoli "Federico II"

  • BSc in Computer Engineering

    Universita' degli Studi di Napoli "Federico II"


Recent Talks

CoVault - A Secure Analytics Platform

Many types of analytics on personal data can be made differentially private, thus alleviating concerns about the privacy of individuals. However, no analytics platform currently exists that can technically prevent data leakage and …

Teaching & Service

Teaching Assistant

Community Service

    SOSP '23 The 29th ACM Symposium on Operating Systems Principles

    Student volunteer

    CMMRS '22 The Cornell, Maryland, Max Planck Pre-doctoral Research School

    Member of the Organizing Committee