Today’s privacy landscape presents a unique set of challenges and opportunities that make this an auspicious time to reshape our data ecosystems for privacy. If interested in working with us in this space, we have several opportunities for master and bachelor thesis projects in the area of data privacy and privacy preserving computations.
Courses
- Seminar on Systems Security, Spring 2023, co-taught with Prof. Shweta Shinde
Student Thesis Projects
- From Threats to Concrete Harms: A New Approach to Privacy Threat Modeling Available
- Scheme-Independent FHE Compiler for TensorFlow Available
- End-to-End System Designs for Privacy Available
- Deploying Secure Computation on Heterogeneous Hardware Available
- Cryptographic Audits for Secure Machine Learning Available
Completed Theses
- Ph.D.
- Master
- Lena Csomor, Bridging the Gap between Privacy Incidents and PETs Thesis
- Christian Knabenhans, Practical Integrity Protection for Private Computations Thesis
- Hidde Lycklama, Scalable and Robust Privacy-Preserving Federated Learning Thesis
- Nicolas Küchler, Enforcement of Privacy Policies via Encryption for Distributed Unbounded Data Thesis
- Patrick Jattke, Analysis, Design and Implementation of Advanced Optimization Strategies for the Marble FHE Compiler Thesis
- Bachelor