Theresa Stadler is a Senior Data Scientist and former postdoctoral researcher at EPFL who specialises in the privacy risks and limits of machine learning and opaque data-processing systems. With a PhD from EPFL and a background in computational neuroscience and biomathematics, she blends rigorous theoretical research with practical experience building privacy-enhancing enterprise software at Privitar. Her work has informed national and European policy and attracted media attention, reflecting a rare talent for translating technical findings into real-world impact. At the Swiss Data Science Center she applies this expertise to production-grade data science, prioritising solutions that balance utility and provable privacy. Colleagues know her for tackling subtle questions—like which learning tasks remain solvable under strict privacy constraints—and turning them into auditable, scalable systems.
6 years of coding experience
13 years of employment as a software developer
Master of Science (MSc) Computational Neuroscience, Master of Science (MSc) Computational Neuroscience at University of Tübingen
Bachelor of Science (B.Sc.) Biomathematics Bioinformatics and Computational Biology, Bachelor of Science (B.Sc.) Biomathematics Bioinformatics and Computational Biology at FAU Erlangen-Nürnberg
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