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Hidde Lycklama
Hidde Lycklama

PhD Student

Hidde Lycklama

I am a third-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 Zürich 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 Holding Secrets Accountable: Auditing Privacy-Preserving Machine Learning

Holding Secrets Accountable: Auditing Privacy-Preserving Machine Learning Paper

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

Preprint, arXiv:2402.15780

Thumbnail of Cohere: Managing Differential Privacy in Large Scale Systems

Cohere: Managing Differential Privacy in Large Scale Systems Paper

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 Github

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.