I am a Computer Science Ph.D. Student at ETH Zürich in the Secure and Private AI (SPY) Lab, advised by Florian Tramèr. My interest is in how the current (and future) research about the security and privacy of machine learning systems can be applied to real-world systems. My research is supported by a CYD Doctoral Fellowship awarded by the armasuisse Cyber-Defence Campus.
Prior to my PhD journey, I earned a Computer Science M.Sc. at EPFL and a Computer Engineering B.Sc. at the Polytechnic University of Turin. I did my Master thesis about the robustness of Vision Transformers supervised by Princeton University’s Prof. Mittal, and I am one of the co-authors and maintainers of RobustBench.
I previously interned as an SWE intern at Bloomberg LP and as a Research Intern at the armasuisse CYD Campus, supervised by Prof. Humbert.
More information can be found on my CV, last updated on 2023/09/26.
- Real-world Machine Learning evasion attacks
- Privacy in Machine Learning
- Security of Large Language Models
Ph.D. in Computer Science, 2022 - Ongoing
ETH Zürich - Swiss Federal Institute of Technology, Zürich, Switzerland 🇨🇭
M.Sc. in Computer Science, 2019 - 2022
EPFL - Swiss Federal Institute of Technology, Lausanne, Switzerland 🇨🇭
B.Sc. in Computer Engineering, 2016 - 2019
PoliTo - Politecnico di Torino, Italy 🇮🇹
News
[04/2024 - Award] Evading Black-box Classifiers Without Breaking Eggs, selected as Distinguished Paper Award Runner-up at IEEE SaTML 2024!
[04/2024 - New Paper: JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models] We have a new paper about benchmarking LLM jailbreak attacks and defenses with a focus on transparency and reproducibility. Take a look here.
[12/2023 - SaTML 2024 news] Presenting Evading Black-box Classifiers Without Breaking Eggs, and co-organizing the LLMs CTF.