Monitoring Concept Drift in Continuous Federated Learning Platforms
IDA 24.04.2024Concept drift has negative effect on continuous FL performance. In this work, we therefore compare different drift detection approaches for FL with dynamic client participation. In particular, we focus on the point in time when different drift detection approaches intervene.
Federated Learning to Improve Counterfactual Explanations for Sepsis Treatment Prediction
AIME 12.06.2023Counterfactual explanations are usually generated with the help of generative models. In order to receive such models, we propose to use federated leaning among hospitals in order to overcome the issue of limited data while data privacy is maintained. Check out our demo to find out more.
Recent Presentations
Predictive Diagnostics for Federated Learning: A Privacy-Preserving Toolbox Towards Successful Federated Learning
ECML PKDD PhD Forum 18.09.2023In order to increase both fairness and success of federated learning prior to actual participation and computation, I aim towards providing privacy-preserving tools in my dissertion, tentatively titled "Predictive Diagnostics in Federated Learning".
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Teaching
Although I am currently not involved in any lectures or seminars, I actively participate in maintaining academic operations in the following capacities:
- Academic Advisor: As such, I am responsible for student consultation and academic advisory for the Master's degree programme in Data Science at Bielefeld University
- Committee Work: I am a representative of the academic middle class in committee work of the Faculty of Technology