Summary
Grzegorz Muszynski is an interdisciplinary AI researcher and applied data scientist with 11+ years of experience translating cutting-edge machine learning, deep learning and causal inference methods into practical solutions for science and industry. His work spans image processing and time-series analytics for climate and extreme-weather risk modeling, including contributions to DOE–Intel and UKRI-funded projects and tools like TECA for extreme climate analysis. He has moved between elite labs and academia—Berkeley Lab/NERSC, British Antarctic Survey, University of Oxford and Edinburgh—bridging academic research and commercial R&D in the insurance sector. Holding a PhD in Computer Science focused on weather-pattern recognition, he combines strong methodological depth (topological data analysis, causal discovery) with product-minded deployment experience. Notably, he pairs domain expertise in atmospheric science with entrepreneurship training from Oxford’s MPLS Enterprise Programme, enabling impact-focused translation of research into real-world risk modelling.
11 years of coding experience
8 years of employment as a software developer
Scientific Entrepreneurship Programme, Scientific Entrepreneurship Programme at University of Oxford, MPLS Enterprise Programme
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Liverpool
Bachelor of Science - Computer Science, Bachelor of Science - Computer Science at Warsaw University of Technology
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Lawrence Berkeley National Laboratory
Polish, English, French