Jesper Dramsch is a Scientist for Machine Learning with 11 years of experience bridging geophysics, academia and industry to deliver practical deep learning solutions for seismic, satellite and weather applications. He holds a PhD in Machine Learning for Geophysics and pioneered transfer learning and GAN-based approaches for seismic interpretation and inversion, while also publishing a 70-year review of ML in geoscience. At ECMWF he designs reproducible ML workflows and curates reference datasets to integrate deep learning into operational forecasting, and his background includes production ML work across space, rail and agricultural projects. A prolific educator and communicator, he teaches data science on Skillshare, runs a popular newsletter and YouTube channel, and contributes to open-source projects like ObsPy. Notably, his work combines physics-aware modeling with pragmatic MLOpsโmaking research methods usable in operational settings.
12 years of coding experience
5 years of employment as a software developer
Heriot-Watt University Edinburgh Campus
Doktor (Ph.D.), Geophysics, Machine Learning in 4D Seismics, Doktor (Ph.D.), Geophysics, Machine Learning in 4D Seismics at Danmarks Tekniske Universitet
High School Exchange, Excellent, High School Exchange, Excellent at Norton High School
ObsPy: A Python Toolbox for seismology/seismological observatories.
Role in this project:
Back-end Developer
Contributions:5 commits, 7 PRs, 10 comments in 1 day
Contributions summary:Jesper primarily focused on fixing documentation and indentation issues within the ObsPy library. The commits modified code related to SEG Y file handling, specifically the `segy.py` file. These changes involved correcting the documentation for the `headonly` parameter and ensuring proper code formatting.
Deep Neural Networks for Map-Based 4D Seismic Pressure-Saturation Inversion
Contributions:1 release, 10 commits, 3 pushes in 2 years 5 months
deep-neural-networks
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