|Name||Jesper Sören Dramsch|
|Research area code||(I4) Artificial intelligence|
|Fellowship Inauguration Year||2022|
Reproducibility for Machine Learning in the Sciences, Physics, Programming, Gaming, Board games, Climbing
Jesper Dramsch works at the intersection of machine learning and physical, real-world data. Currently, they're working as a scientist for machine learning in numerical weather prediction at the coordinated organisation ECMWF.
Before, Jesper has worked on applied exploratory machine learning problems, e.g. satellites and Lidar imaging on trains, and defended a PhD in machine learning for geoscience. During the PhD, Jesper wrote multiple publications and often presented at workshops and conferences, eventually holding keynote presentations on the future of machine learning.
Moreover, they worked as consultant machine learning and Python educator in international companies and the UK government. Their courses on Skillshare have been watched over 25 days by over 2000 students. Additionally, they create educational notebooks on Kaggle, reaching rank 81 worldwide.
|Title||Start date||End date|
|CW23||Tuesday, 02 May 2023||Thursday, 04 May 2023|
|ML.Recipes a Jupyter Book to make ML reproducible in science||Monday, 06 March 2023||Wednesday, 05 March 2025|
|Speedrunning a Workshop on Reproducibility for Machine Learning in Science||Friday, 10 March 2023|
|How to increase citations, ease reviews and facilitate collaboration for ML in applied science||Monday, 13 February 2023|
|https://docs.google.com/document/d/1vqiJ4F1v7PZs4XoBQns5BgF2cymKVCcZ7qn0vV5th4A/edit?usp=sharing||Monday, 12 December 2022|