Summary
Sebastian Szyller is a tenure-track Assistant Professor at Aalto University and leader of the Trustworthy & Adversarial Computing Lab, with 11 years of experience at the intersection of machine learning, security, and privacy. His research focuses on trustworthy ML for large language and vision models, covering robustness, adversarial attacks, provenance, watermarking and unlearning, and he has driven applied projects at Intel Labs on LLM privacy and RAG integrity. He earned a PhD in Computer Science studying model confidentiality, model extraction and ownership verification, and has contributed practical tools and prototypes for provenance and model auditing. Sebastian blends academic rigor with industry-facing engineering, having moved from Big Data/Scala engineering to research roles that emphasize both differential privacy and operational defenses. Based in Helsinki, he is known for bridging theoretical attacks with deployable mitigations and for representing technical communities in standards work around provenance. Colleagues describe him as a researcher-engineer who favors reproducible tooling and measurable protections over purely theoretical claims.
11 years of coding experience
9 years of employment as a software developer
Doctor of Science - PhD, Computer Science (Security and Privacy of Machine Learning), Doctor of Science - PhD, Computer Science (Security and Privacy of Machine Learning) at Aalto University
Bachelor of Science (B.Sc.), Computer Science, Bachelor of Science (B.Sc.), Computer Science at Lodz University of Technology
Erasmus+ Exchange, Computer Science, Erasmus+ Exchange, Computer Science at Turku University of Applied Sciences
English, Polish, German, Spanish, Finnish