With a background in theoretical computer science, I work on formal methods and artificial intelligence. My research draws on logic, automata theory, and synthesis to study the verification, explainability, and interpretability of AI systems. I am part of the PEPR IA SAIF project and the FM4AI group at LMF.

Current research interests

• logical foundations of distributed and multi-agent systems

• formal methods for machine learning and agentic AI, including explainability, verification, and reliable interaction between agents

• synthesis, planning, and grammatical inference

• ZipperGen, a Python DSL for specifying and executing reliable LLM-agent workflows from a global description (interactive demo, GitHub)