Dr. Tobias Weigel
• Hybrid and large machine learning models
• Machine Learning on remote sensing data
• Intelligent middleware and workflow automation
• Service- and community-building
| Since 2025 | Department head AI Consulting | Hereon |
|---|---|---|
| 2020-2024 | Group leader Helmholtz AI Consulting | Deutsches Klimarechenzentrum, Hamburg |
| 2012-2015 | Computer Science (PhD) | University of Hamburg |
| 2010-2020 | Research software engineer | Deutsches Klimarechenzentrum, Hamburg |
| 2004-2010 | Diplom Geoinformatics | University of Münster |
- Alrabayah, O.,Caus, D.,Watson, R.A.,Schulten, H.Z.,Weigel, T.,Rüpke, L.,Al-Halbouni, D. (2024): Deep-Learning-Based Automatic Sinkhole Recognition: Application to the Eastern Dead Sea. Remote Sensing, Vol. 16, 13, 2264, MDPI, Basel. https://doi.org/10.3390/rs16132264
- Arnold, C.,Sharma, S.,Weigel, T.,Greenberg, D.S. (2024): Efficient and stable coupling of the SuperdropNet deep-learning-based cloud microphysics (v0.1.0) with the ICON climate and weather model (v2.6.5). Geoscientific Model Development, Vol. 17, 9, 4017-4029, EGU - Copernicus Publication, Katlenburg-Lindau. https://doi.org/10.5194/gmd-17-4017-2024
- Karimpouli, S.; Caus, D.; Grover, H.; Martínez-Garzón, P.; Bohnhoff, M.; Beroza, G.C.; Dresen, G.; Goebel, T.; Weigel, T.; Kwiatek, G. (2023): Explainable machine learning for labquake prediction using catalog-driven features, Earth and Planetary Science Letters, Volume 622, 118383, https://doi.org/10.1016/j.epsl.2023.118383
- Piraud, M.; Camero, A.; Götz, M.; Kesselheim, S.; Steinbach, P.; Weigel, T. (2023): Providing AI expertise as an infrastructure in academia, Patterns, Volume 4, Issue 8, 2023, 100819, https://doi.org/10.1016/j.patter.2023.100819
- Weigel, Schwardmann, Klump, Bendoukha, Quick: Making Data and Workflows Findable for Machines. Data Intelligence (2020). https://doi.org/10.1162/dint_a_00026