We supervise the following theses within the TUHH:

• Gabriel Storch: Meta-reinforcement learning for program estimation in the ARC-AGI corpus (Master's thesis)
• Ibrahim Kalil: Single-to-Multi-Label classification with logical constraints (Master's thesis)
• Hojat Noghavi: Interpretation of level-k user feedback for interactive clustering (Master's thesis)
• Rishi Tank: Inverse reinforcement learning with reward switching (Master's thesis)
• Abdelrahman Yousef: Reproducing and extending LADDER+TTRL (Master's thesis)
• Varad Kulkarni: Music Recommendation with Fairness Constraints for Artists (Master's thesis)
• Pia Borchers: Speech recognition for Low German (Bachelor's thesis)
• Till Schwiers: Analogical reasoning with world models
• Mounika Tirupathiraju Buddharaju: Reward design using Large Language Models
• Krishnan Lakshmanan Ananya: 
• Soumobrata Mukherjee: Hierarchical planning of learning sessions for model-based teaching scenarios
• Konrad Frank: Bayesian reconstitution of 3D scenes from 2D images

We supervised the following theses:

• Paulina Vennemann: Learning optimal hyperparameters for clustering based on incomplete user feedbacks (Master's thesis)

We also received the visit of Lucas Martens and Moritz Haußner.