Vitus Benson

Hi Friend, great to have you here!

I am Vitus, currently an ELLIS PhD candidate at Max Planck Institute for Biogeochemistry, ELLIS Unit Jena and ETH Zürich. I am conducting my research under the supervision of Markus Reichstein and Fanny Yang.

I train deep neural networks on data of the Earth system. More specifically, I am focusing on two applications. On the one hand, I am interested in the applicability of large-scale AI to Early Warning Systems. Within the EarthNet initiative we are leveraging high resolution satellite imagery to build data-driven impact early warning systems – with applications to anticipatory action for droughts and heat waves. On the other hand, as part of the AI4Carbon Community Initiative I explore the use of deep neural networks for carbon cycle research. In particular, I am assessing the use of AI for atmospheric transport and inverse modeling – analogous to how recent works have revolutionized numerical weather prediction and other areas of scientific machine learning.

My research interests are broadly speaking Deep Learning, Biogeochemistry, Climate Risk Mitigation and Complex Systems. I believe solving global challenges requires working together. Let us do just that!

news

Aug 28, 2025	Together with my amazing colleagues within EarthNet Team I attended the first WeatherGenerator Hackathon in Bonn.
Aug 27, 2025	I have the pleasure to give the final presentation during the Machine Learning for the Earth System workshop in Bonn.
Jul 05, 2025	Honored to be contributing to the experimental jazz performances Don’t Worry It’s Out of Control in Arnstadt & Jena with an introductory foreword on climate science (in German).
Jun 30, 2025	Recent developments in Machine Learning for Atmospheric Carbon Cycle Science will be covered in my talk at the CMCC Workshop on AI for Carbon.
Jun 26, 2025	Happy to be presenting our vision on Land Surface Foundation models at the ESA Living Planet Symposium 2025.
Jun 10, 2025	Glad to co-organize the Artificial Intelligence in Anticipatory Action workshop with colleagues from German Red Cross, HeiGIT, IFRC and WFP.

TEDx talk

selected publications

Nat. Commun.

Early warning of complex climate risk with integrated artificial intelligence

Markus Reichstein* , Vitus Benson* , Jan Blunk , Gustau Camps-Valls , Felix Creutzig , and 14 more authors

Nature Communications, Mar 2025

Bib PDF

@article{reichstein2025ews,
  title = {Early warning of complex climate risk with integrated artificial intelligence},
  author = {Reichstein*, Markus and Benson*, Vitus and Blunk, Jan and Camps-Valls, Gustau and Creutzig, Felix and Fearnley, Carina J and Han, Boran and Kornhuber, Kai and Rahaman, Nasim and Sch{\"o}lkopf, Bernhard and Tárraga, José María and Frank, Dorothea and Martini, Giulia and Vinuesa, Ricardo and Dall, Karen and Denzler, Joachim and Nganga, Naomi and Maddix Robinson, Danielle and Weldemariam, Kommy},
  journal = {Nature Communications},
  volume = {16},
  number = {1},
  pages = {2564},
  year = {2025},
  month = mar,
  publisher = {Nature Publishing Group UK London},
}

JAMES

Atmospheric Transport Modeling of CO2 with Neural Networks

Vitus Benson , Ana Bastos , Christian Reimers , Alexander J. Winkler , Fanny Yang , and 1 more author

Journal of Advances in Modeling Earth Systems, Feb 2025

Bib PDF Code

@article{benson2024neuraltransport,
  title = {Atmospheric Transport Modeling of CO2 with Neural Networks},
  author = {Benson, Vitus and Bastos, Ana and Reimers, Christian and Winkler, Alexander J. and Yang, Fanny and Reichstein, Markus},
  year = {2025},
  month = feb,
  pages = {e2024MS004655},
  journal = {Journal of Advances in Modeling Earth Systems},
  volume = {17},
  number = {2},
  publisher = {Wiley Online Library},
}

CVPR

Multi-modal Learning for Geospatial Vegetation Forecasting

Vitus Benson , Claire Robin , Christian Requena-Mesa , Lazaro Alonso , Nuno Carvalhais , and 5 more authors

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2024

Bib PDF Code

@article{benson2024multimodal,
  title = {Multi-modal Learning for Geospatial Vegetation Forecasting},
  author = {Benson, Vitus and Robin, Claire and Requena-Mesa, Christian and Alonso, Lazaro and Carvalhais, Nuno and Cort\'es, Jos\'e and Gao, Zhihan and Linscheid, Nora and Weynants, M\'elanie and Reichstein, Markus},
  year = {2024},
  month = jun,
  pages = {27788-27799},
  journal = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
}