I am a PhD candidate at Radboud University working on applying AI and large language models to analyze web and mobile ecosystems. My research combines large-scale web measurement, data collection, and AI techniques to detect privacy violations across websites and mobile applications.
Backed by publications at IEEE S&P and ACM CCS, I combine strong research depth with hands-on experience.
Alongside my academic work, I collaborate with industry on applied privacy and AI systems. I currently work as a consultant with VaultJS in the United States and previously completed an industry internship at ING, where I built multi-agent retrieval-augmented pipelines for automated code understanding and modernization of large legacy codebases.
Large-scale web measurement studies to detect online tracking and advertising using ML. Published at IEEE S&P and ACM CCS.
Advising on mobile app privacy research, including AI-driven app navigation.
Developing a multi-agent system with Retrieval-Augmented Generation (RAG) for automated code understanding and modernization.
Developed an iOS automation library that leverages large language models and accessibility features to navigate mobile apps and analyze in-app advertisements.
Applied Deep Learning to therapeutic antibody discovery in a biotech research team.