We supervise the following theses within the TUHH:

• 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)
• Hojat Noghavi: Interpretation of level-k user feedback for interactive clustering (Master's thesis)
• 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)
• Rishi Tank: Inverse reinforcement learning with non-stationary goals (Master's thesis)
• Varad Kulkarni: The Artist-Listener Paradox: Ethical Algorithmic Redesign for Music Recommendation Systems (Master's thesis)
• Pia Borchers: Adapting ASR Foundation Models for Low-Resource Languages: The Case of Low German (Bachelor's thesis)
• Basma Almahmoud: Context-Aware Machine Translation through RAG-Enhanced Large Language Models (Master's thesis)

We also received the visit of Elif Duman, Zeynep Tasevli, Lucas Martens and Moritz Haußner.