Kleomenis Katevas is a Principal Machine Learning Researcher based in London with 11 years of experience building privacy-preserving and on-device ML systems, currently leading the ML Research team at Brave. He specializes in foundation models, fine-tuning, and model distillation with a practical focus on efficiency and deployability of LLMs and cross-encoders. His work spans federated and P2P learning, trusted execution environments, and mobile sensing—areas informed by research roles at Telefonica, Imperial College, and a PhD from Queen Mary University of London. He has a strong product and startup background as co-founder/CTO of a successful geolocation app and is the author of SensingKit, an open-source mobile sensing framework. Known for translating academic research into deployed systems (e.g., NHS-used clinical apps and distributed edge frameworks), he blends rigor with hands-on engineering for privacy-first ML.
11 years of coding experience
15 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Queen Mary University of London
BSc, Informatics Engineer of Technological Education (T.E.), BSc, Informatics Engineer of Technological Education (T.E.) at Alexander Technological Educational Institute of Thessaloniki
An iOS library that provides Continuous Sensing functionality to your applications.
Contributions:10 releases, 316 commits, 12 PRs in 7 years 7 months
ios-librarysensingcontinuousswiftios
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Kleomenis Katevas - Principal Machine Learning Researcher at Brave