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.