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Hidde Lycklama
Hidde Lycklama

PhD Student

Hidde Lycklama

I am a fourth-year Ph.D. student at the Privacy Preserving Systems Lab. My research focuses on the robustness of secure collaborative learning systems. My goal is to develop a rigorous understanding of secure collaborative learning systems' robustness and to devise solutions to manage and alleviate integrity issues in these systems. I completed my M.Sc. degree at ETH Zurich in Computer Science. Before that, I graduated cum laude with honors at the Delft University of Technology with a B.Sc in Computer Science.

Talks:

Holding Secrets Accountable: Auditing Private ML Algorithms

RoFL: Robustness of Secure Federated Learning

Camel: Collaborative Audits for Machine Learning

Teaching:

  • Data Structures and Algorithms (2024SS)
  • Advanced Operating Systems (2022SS, 2023SS)
  • Computer Systems (2021FS, 2022FS, 2023FS)
  • Computer Science for ITET (2021SS)

Publications:

Thumbnail of Artemis: Efficient Commit-and-Prove SNARKs for zkML

Artemis: Efficient Commit-and-Prove SNARKs for zkML Paper Github

Hidde Lycklama*, Alexander Viand*, Nikolay Avramov, Nicolas Küchler, Anwar Hithnawi

Preprint, arXiv:2409.12055

Thumbnail of UTrace: Poisoning Forensics for Private Collaborative Learning

UTrace: Poisoning Forensics for Private Collaborative Learning Paper

Evan Rose, Hidde Lycklama, Harsh Chaudhari, Anwar Hithnawi, Alina Oprea

Preprint, arXiv:2409.15126

Thumbnail of Holding Secrets Accountable: Auditing Privacy-Preserving Machine Learning

Holding Secrets Accountable: Auditing Privacy-Preserving Machine Learning Paper Slides Github

Hidde Lycklama, Alexander Viand, Nicolas Küchler, Christian Knabenhans, Anwar Hithnawi

USENIX Security 2024.

Thumbnail of Cohere: Managing Differential Privacy in Large Scale Systems

Cohere: Managing Differential Privacy in Large Scale Systems Paper Slides Video

Nicolas Küchler, Emanuel Opel, Hidde Lycklama, Alexander Viand, Anwar Hithnawi

IEEE Security and Privacy (Oakland) 2024.

Thumbnail of RoFL: Robustness of Secure Federated Learning

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.

Thumbnail of Cryptographic Auditing for Collaborative Learning

Cryptographic Auditing for Collaborative Learning Paper

Hidde Lycklama, Nicolas Küchler, Alexander Viand, Emanuel Opel, Lukas Burkhalter, Anwar Hithnawi

ML Safety Workshop at NeurIPS 2022

Thumbnail of Decreg: A framework for preventing double-financing using blockchain technology

Decreg: A framework for preventing double-financing using blockchain technology Paper

Hidde Lycklama, Joris Oudejans, Zekeriya Erkin

ACM Workshop on Blockchain, Cryptocurrencies and Contracts 2017. Abu Dhabi.