PrivML Research Group
This page provides an overview on current activities of the PrivML research group I am coordinating. The topics are mainly (but not exclusively) centered around privacy-preserving machine learning.
Currently ongoing theses
Student | Program | Topic |
---|---|---|
C. Müller | Master | Personalized Differential Privacy |
W. Gu | Bachelor | Differential Private Synthetic Data Generation |
T. Känel | Bachelor | Practical Evaluation of Neural Network Watermarking |
J. Ihring | Master | Privacy Quantification Methods |
O. Bouanani | Bachelor | Neural Network Architectural Choices for Privacy |
D. Wang | Bachelor | Novel Methods for Neural Network Watermarking |
D. Sosnovchyk | Bachelor | Synthetic Data Privacy Evaluation |
Past theses
Student | Program | Thesis Title |
---|---|---|
M. Krüger | Bachelor | Application and Evaluation of Differential Privacy in Health Data Classification Tasks |
Open topics
Currently, the following topics are available:
- Side Channel Attacks against Neural Networks (Master)
- Bias in AI (Bachelor/Master)
For a concrete description of the topics, please get in touch.