Kathrin Stark

Kathrin Stark serves as an Assistant Professor in the Department of Computer Science within the School of Mathematical & Computer Sciences. Her research bridges theoretical computer science and practical AI systems through rigorous formal verification methodologies.

Her primary research domains include Formal Verification, Programming Languages, Machine Learning, and Neural Networks, with specialized expertise in Coq-based theorem proving. She focuses on developing mathematically verified tools for critical AI components, particularly targeting neural network verification and differentiable logic frameworks.

Recent publications (2023-2025) reveal a concentrated research trajectory in applying formal methods to machine learning safety. Key themes include verified foreign function interfaces, certified proof checkers for deep neural networks, and semantic foundations for differentiable logics – demonstrating how theorem proving can enhance reliability in AI systems.