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, I study the carbon cycle with neural network emulators. 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 21, 2024	New preprint alert: Atmospheric Transport Modeling of CO2 with Neural Networks is on ArXiv now!
Aug 02, 2024	At ICDC 11 in Manaus, i’ll give the last talk, see you there!
Jun 28, 2024	I am attending the ELLIS Community event in Helsinki, briefly introducing our activities on AI for Early Warning.
Jun 22, 2024	I’ll present our work on Multi-modal learning for geospatial vegetation forecasting virtually at CVPR!
Jun 06, 2024	I’m back in Jena for the Hybrid Modelling Workshop, with some fresh thoughts on hybrid atmospheric transport!
May 31, 2024	If you are in Geneva, the AI for Good Workshop on Early Warning is worth checking out – I’ll talk about EarthNet!

selected publications

ArXiv

Atmospheric Transport Modeling of CO2 with Neural Networks

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

arXiv, Aug 2024

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 = {2024},
  month = aug,
  pages = {2408.11032},
  journal = {arXiv},
}

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)},
}

ERL

Measuring Tropical Rainforest Resilience under Non-Gaussian Disturbances

Vitus Benson , Jonathan F. Donges , Niklas Boers , Marina Hirota , Andreas Morr , and 3 more authors

Environmental Research Letters, Jan 2024

Bib PDF Code

@article{benson.etal_2024,
  title = {Measuring Tropical Rainforest Resilience under Non-{{Gaussian}} Disturbances},
  author = {Benson, Vitus and Donges, Jonathan F. and Boers, Niklas and Hirota, Marina and Morr, Andreas and Staal, Arie and Vollmer, Jürgen and Wunderling, Nico},
  year = {2024},
  month = jan,
  journal = {Environmental Research Letters},
  volume = {19},
  number = {2},
  pages = {024029},
  publisher = {{IOP Publishing}},
  doi = {10.1088/1748-9326/ad1e80},
}