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. My research is published in leading academic venues such as ACM CCS and IEEE S&P.
Alongside my academic work, I collaborate with industry on applied privacy and AI systems. I currently work as a consultant with VaultJS (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 AI-driven mobile app privacy analysis, including evaluation of LLM-based navigation agents for automated app exploration and security assessment.
Developed 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.