| 2024 | GI | Privacy, Utility, Effort, Transparency and Fairness: Identifying and Swaying Trade-offs in Privacy Preserving Machine Learning through Hybrid Methods. | Marian Eleks, Ihler Jakob, Jonas Rebstadt, Henrik Kortum-Landwehr, Oliver Thomas |
| 2023 | GI | Privacy Aware Processing. | Marian Eleks, Jonas Rebstadt, Henrik Kortum, Oliver Thomas |
| 2022 | CaiSE | Towards Explainable Artificial Intelligence in Financial Fraud Detection: Using Shapley Additive Explanations to Explore Feature Importance. | Philipp Fukas, Jonas Rebstadt, Lukas Menzel, Oliver Thomas |
| 2022 | GI | Learning without Looking: Similarity Preserving Hashing and Its Potential for Machine Learning in Privacy Critical Domains. | Marian Eleks, Jonas Rebstadt, Philipp Fukas, Oliver Thomas |
| 2022 | GI | Towards the Operationalization of Trustworthy AI: Integrating the EU Assessment List into a Procedure Model for the Development and Operation of AI-Systems. | Henrik Kortum, Jonas Rebstadt, Tula Bschen, Pascal Meier, Oliver Thomas |
| 2022 | WI | Proposing a Roadmap for Designing Non-Discriminatory ML Services: Preliminary Results from a Design Science Research Project. | Henrik Kortum, Philipp Fukas, Jonas Rebstadt, Marian Eleks, Marjan Nobakht Galehpardsari, Oliver Thomas |
| 2022 | WI | Towards Personalized Explanations for AI Systems: Designing a Role Model for Explainable AI in Auditing. | Jonas Rebstadt, Florian Remark, Philipp Fukas, Pascal Meier, Oliver Thomas |
| 2021 | GI | Towards a transparency-oriented and integrating Service Registry for the Smart Living Ecosystem. | Jonas Rebstadt, Henrik Kortum, Simon Hagen, Oliver Thomas |