Published multiple papers, including 'Trust Me, I Know the Way: Predictive Uncertainty in the Presence of Shortcut Learning', 'Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning', etc.
Research Experience
Active in research subgroups such as Probabilistic Machine and Deep Learning and Causal and Fair Machine Learning.
Education
Started as a PhD student at the Statistical Learning & Data Science working group in February 2022; obtained a Bachelor's degree (B.A.) in Business Administration from DHBW Ravensburg and a Bachelor's and consecutive Master's degree (B.Sc., M.Sc.) in Statistics from LMU Munich. Advisor: Prof. David Rügamer.
Background
Research Interests: Predictive uncertainty and probabilistic machine learning, Bayesian neural networks, Symmetries and posterior landscapes, Overparameterization and generalization, Distributional robustness and causal inference. Professional field: Statistics.