Marie Roald is an information technologist and data scientist with 11 years of experience combining academic rigour and practical engineering, currently working at the National Library of Norway. She holds a PhD in data mining and has published multiple papers on temporal data mining while contributing reproducible scientific software and open-source machine learning code such as PARAFAC2 support in the TensorLy library. Equally at home teaching beginners and developing curricula, she has extensive experience creating programming courses and outreach materials for non-technical audiences. Marie prioritizes maintainable code, clear communication, and visualization to make complex models accessible, and she brings a rare blend of research depth and hands-on production engineering to data-driven projects.
11 years of coding experience
Doctor of Philosophy - PhD, Data mining, Doctor of Philosophy - PhD, Data mining at SimulaMet/OsloMet
Contributions:19 reviews, 114 commits, 14 PRs in 3 years
Contributions summary:Marie implemented features for the PARAFAC2 decomposition algorithm within the TensorLy library. They added options for initializing the decomposition using specified methods and contributed the initial implementation of the PARAFAC2 algorithm. Further contributions included adding default values for the random_parafac2 arguments and fixing tests for the PARAFAC2 tensor.
Contributions:1 release, 24 commits, 2 PRs in 1 year 4 months
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