Maciej Skórski is a research-driven scientist and engineer with 8+ years blending academic depth and industry impact across cryptography, information theory, applied statistics and machine learning. He has held post-doc and research roles at top institutions and translated that expertise into production ML and data-engineering work—building Azure ML pipelines, EHR predictive models, and efficient statistical evaluation tooling. Equally comfortable proving theorems and shipping ETLs, he has contributed to hardware RNG analysis, second-order neural optimization research, and cryptographic R&D for startups. Based in Luxembourg, he combines a PhD-level foundation with hands-on experience in deployment, mentorship, and grant-winning technical leadership. A detail that often surprises collaborators: he moves seamlessly between formal probabilistic modelling and pragmatic pipeline engineering, making him effective at both foundational research and product-ready systems.
9 years of coding experience
8 years of employment as a software developer
Master of Science (M.S.), Mathematics and Computer Science, Master of Science (M.S.), Mathematics and Computer Science at University of Warsaw
Data and code to design and evaluate the PLL-based true random number generator according to the paper "Enhancing Quality and Security of the PLL-TRNG" (published at TCHES 2023).
Contributions:11 releases, 23 PRs, 133 pushes in 1 year 1 month
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