Nicolas Küchler
I'm a fourth-year Ph.D. student in the Privacy Preserving Systems Lab at ETH Zurich. My research interests lie broadly at the intersection of computer systems and data privacy. I design and build systems that follow a user-centric privacy model to enable users to exercise more control over their data. More recently, I'm interested in addressing the challenges of deploying differential privacy at scale. I completed my M.Sc degree in Computer Science at ETH Zurich with distinction. Before that, I graduated summa cum laude from the University of Zurich with a B.Sc degree in Informatics.
Talks:
Cohere: Managing Differential Privacy in Large Scale Systems.
- IEEE Security & Privacy 2024, San Francisco, [Video, Slides, GitHub]
- TPDP'24, Boston, Poster Session
- ETH Zurich, Systems Lunch Seminar
Zeph: Cryptographic Enforcement of End-to-End Data Privacy.
- Stanford, Security Lunch Seminar
- USENIX OSDI'21, Online, [Video, Slides, GitHub]
- UC Berkeley, CA, NetSys Lunch Seminar
- ETH Zurich, Systems Lunch Seminar
- ETH Zurich, Applied Crypto Group
The Privacy Management Layer.
- USENIX Security'22, Boston, Poster Session
DoE-Suite: A tool for remote experiment management.
- ETH Zurich, Systems Lunch Seminar, [Slides, Github]
Teaching:
- Computer Science for MAVT / ITET (2021, 2022, 2023, 2024 @ ETH)
- Systems Programming and Computer Architecture (2020, 2021, 2022, 2023 @ ETH)
- Informatics I (2015 @ UZH)
Publications:
Artemis: Efficient Commit-and-Prove SNARKs for zkML Paper Github
Hidde Lycklama*, Alexander Viand*, Nikolay Avramov, Nicolas Küchler, Anwar Hithnawi
Preprint, arXiv:2409.12055
Holding Secrets Accountable: Auditing Privacy-Preserving Machine Learning Paper Slides Github Video
Hidde Lycklama, Alexander Viand, Nicolas Küchler, Christian Knabenhans, Anwar Hithnawi
USENIX Security 2024.
Cohere: Managing Differential Privacy in Large Scale Systems Paper Slides Github Video
Nicolas Küchler, Emanuel Opel, Hidde Lycklama, Alexander Viand, Anwar Hithnawi
IEEE Security and Privacy (Oakland) 2024.
RoFL: Robustness of Secure Federated Learning Paper Slides Github Video
Hidde Lycklama*, Lukas Burkhalter*, Alexander Viand, Nicolas Küchler, Anwar Hithnawi
IEEE Security and Privacy (Oakland) 2023.
Cryptographic Auditing for Collaborative Learning Paper Poster
Hidde Lycklama, Nicolas Küchler, Alexander Viand, Emanuel Opel, Lukas Burkhalter, Anwar Hithnawi
ML Safety Workshop at NeurIPS 2022
Zeph: Cryptographic Enforcement of End-to-End Data Privacy. Paper Slides Github Video
Lukas Burkhalter*, Nicolas Küchler*, Alexander Viand, Hossein Shafagh, Anwar Hithnawi
USENIX OSDI 2021.