Jesper Dramsch

Jesper Dramsch

Jesper Dramsch works at the intersection of machine learning and physical, real-world data. Currently, they work as a scientist for machine learning for numerical weather prediction at the Coordinated Organisation ECMWF, where they’re involved in the development of AIFS and the software architecture of Anemoi.

Jesper is co-chair of the Working Group on Modelling for the UN ITU Global Initiative on Resilience to Natural Hazards through AI Solutions. They’re a 2022 fellow of the Software Sustainability Institute, creating awareness and educational resources, such as https://ml.recipes, around the reproducibility of machine learning results in applied science. Previously, they have worked on applied exploratory machine learning problems, such as satellite and Lidar imaging on trains, and defended a PhD in machine learning for geoscience at the Technical University of Denmark. During the PhD, Jesper wrote multiple publications and often presented at workshops and conferences, eventually holding keynote presentations on the future of machine learning in geoscience.

Moreover, they create educational content in the form of notebooks on Kaggle, applying machine learning to various domains, and achieve a rank of 81 worldwide out of over 100,000 participants. Their video courses on Skillshare have been watched for over 6,500 hours by more than 11,000 students. Jesper was invited into the YouTube Partner program for their videos on programming, machine learning, and tech. They also write a weekly newsletter to over 1,111 subscribers about non-hype AI at https://late.email.

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  • Organization
    ECMWF
  • Profession
    Scientist
Related sessions
In person
7 July 2026
09:00 - 12:15
EST - New York
CST - Beijing
PST - Los Angeles
AWST - Perth, Australia

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