Summary
Lukas Zierahn is a postdoctoral researcher and machine learning practitioner with eight years of experience bridging theoretical mathematics and applied ML, currently working jointly at CWI and Booking.com on Best-Arm Identification in non-stationary, expert and missing-context settings. He holds advanced degrees from UCL and Milano and a First Class Mathematics BA from Lancaster, bringing deep statistical foundations to practical research problems. Lukas has applied his expertise in industry settings including AWS, where he developed practical bandit solutions for LLM prompt selection and evaluation on real-world benchmarks. His background includes building production-ready change-point estimation tools during an EPSRC internship that culminated in multi-language releases (Go/Python/R) and CRAN publication. Comfortable across research and engineering, he combines rigorous algorithm design with software/engineering pragmatism from full-stack internships and collaborative projects. Colleagues describe him as someone who turns abstract bandit and RL theory into robust, deployable solutions for complex, noisy environments.
8 years of coding experience
1 year of employment as a software developer
University of Milan
Bachelor's degree, Mathematics, First Class Honours, Aggregation Score: 20.2, Bachelor's degree, Mathematics, First Class Honours, Aggregation Score: 20.2 at Lancaster University
Bachelor of Science - BS, Mathematics, Bachelor of Science - BS, Mathematics at University of Hamburg
University College London
German, English