Summary
Martin Tveten is a senior researcher based in Oslo with 8 years of experience specializing in time series analysis, changepoint and anomaly detection, and streaming data for industrial applications. At Norsk Regnesentral he develops practical, production-ready methods and maintains skchange, a fast Python library for changepoint and collective anomaly detection. He holds advanced training in modelling and data analysis from the University of Oslo and completed a PhD there, combining strong mathematical foundations with applied engineering. Martin’s background also includes leadership and operational experience running large volunteer organisations and managing multimillion-kroner budgets, which informs his pragmatic, impact-focused approach to research and deployment.
8 years of coding experience
Master's degree, Modellering og dataanalyse, Master's degree, Modellering og dataanalyse at Universitetet i Oslo (UiO)
Bachelor's degree, Matematikk, informatikk og teknologi, Bachelor's degree, Matematikk, informatikk og teknologi at Universitetet i Oslo / University of Oslo (UiO)