The Secure, Reliable, and Intelligent Systems (SRI) Lab is a research
group in the Department of Computer Science at ETH
Zurich.
Our research focuses on reliable, secure, and trustworthy machine learning, with emphasis on large language
models.
We currently study issues of controllability, security and privacy, and reliable
evaluation of LLMs, their application to mathematical reasoning and coding, as well as generative AI
watermarking, AI regulations, federated learning privacy, robustness and
fairness certification, and quantum computing.
Our work has led to six ETH spin-offs:
NetFabric (AI for systems),
LogicStar (AI code agents),
LatticeFlow (robust ML),
InvariantLabs (secure AI agents; acquired),
DeepCode (AI for code; acquired),
and ChainSecurity (security verification; acquired).
To learn more about our work see our Research page, recent Publications, and GitHub
releases. To stay up to date follow our group on Twitter.
Latest News
12.04.2026
SRI Lab is presenting 8 papers at the main track of ICLR 2026 in Rio de Janeiro, Brazil. Two papers have been awarded with an oral presentation.
24.02.2026
Our work on the effect of context files on coding agents trends on X (formerly Twitter) and HackerNews after being featured in several high-profile YouTube videos.
Most Recent Publications
AutoBaxBuilder: Bootstrapping Code Security Benchmarking
Tobias von Arx, Niels Mündler, Mark Vero, Maximilian Baader, Martin Vechev
ICML
2026
Adaptive Generation of Bias-Eliciting Questions for LLMs
Robin Staab, Jasper Dekoninck, Maximilian Baader, Martin Vechev
ICML
2026
BrokenMath: A Benchmark for Sycophancy in Theorem Proving with LLMs
Ivo Petrov, Jasper Dekoninck, Martin Vechev
ICML
2026
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