Christoph Weinhuber
I am a second-year PhD student at the University of Oxford, where I study Artificial Intelligence with a focus on decision-making under uncertainty and long-term goal reasoning. I currently work at Intrinsic, an AI robotics group at Google. My research focuses on agentic AI, stochastic planning and reinforcement learning, often involving temporally extended goals expressed through logics. Check out this video, if you want to learn more about my research. I am very fortunate to be supervised by Giuseppe De Giacomo, Dave Parker and Alessandro Abate.
Publications
- Formal Foundations of Agentic Business Process Management
- Semantically Labelled Automata for Multi-Task Reinforcement Learning with LTL Instructions
- Multi-Property Synthesis
- Good-for-MDP State Reduction for Stochastic LTL Planning
- A Requirements Engineering-Driven Methodology for Planning Domain Generation via LLMs with Invariant-Based Refinement
- Emerson-Lei and Manna-Pnueli Games for LTLf+ and PPLTL+ Synthesis
- Solving MDPs with LTLf+ and PPLTL+ Temporal Objectives
- Explaining Control Policies through Predicate Decision Diagrams
- Code Simulation as a Proxy for High-order Tasks in Large Language Models
- Code simulation challenges for large language models
- Federated learning with swift: An extension of flower and performance evaluation
- Language models as a service: Overview of a new paradigm and its challenges
- dtControl 2.0: explainable strategy representation via decision tree learning steered by experts