QUESTIONS & CONNECTIONS
Mathematical structures, formal methods, and their role in AI.
My path through mathematics, philosophy, and computer science centres on how we represent knowledge—and how we reason with norms.
I study algebraic semantics for normative systems, connecting input/output logic with modal logic. This work characterizes obligations and permissions through the mathematical structures that represent them.
Explore the mathematical foundations ↓I investigate how conditional norms generate obligations and how permissions interact with them. My work extends input/output logic with preferences to study normative reasoning under uncertainty.
Explore normative reasoning ↓I formalize normative logics in higher-order logic and explore them with Isabelle/HOL. My contributions to the LogiKEy Workbench support automated reasoning about ethical and legal theories.
Explore automated reasoning ↓I combine language models with theorem provers for verifiable natural language inference. My collaborative work makes the choice of logic explicit and examines its effect on normative reasoning and proof behavior.
Explore neuro-symbolic AI ↓RESEARCH DIRECTION · PROPOSED PROJECT
How can normative knowledge be tested and maintained as its sources and interpretations change?
NORMTRACK proposes a workflow connecting AI-assisted knowledge construction, formal testing, versioning, and expert review. It builds on existing formal foundations and a proof of concept; the integrated environment remains to be developed and validated.