Christian Reimers

Christian Reimers is a Project Group Leader and PostDoc at the Department Biogeochemical Integration (BGI) of the Max Planck Institute for Biogeochemistry in Jena, Germany. He leads the Project Group Adapting Machine Learning for Earth Systems and contributes to the Research group Atmosphere-Biosphere Coupling, Climate and Causality, focusing on integrating machine learning with Earth systems research.

• Education: M.Sc. and B.Sc. in Mathematics from Georg-August-University, Göttingen (2013-2017, 2011-2013)

His research lies at the intersection of machine learning, causal modeling, and Earth system science. Recent work explores hybrid physics-AI models for evapotranspiration and carbon cycle dynamics, spatiotemporal deep learning for climate teleconnections, and bias mitigation in neural network classifiers. Publications span climate informatics, phenology modeling, and neural network interpretability.

Key trends in his 15 most recent articles (2018-2025) include: deep learning architectures for Earth observation; causal inference in climate-vegetation interactions; hybrid modeling combining physics and data-driven approaches; and bias detection in medical imaging applications. His work often addresses interpretability challenges in black-box models.

Current affiliations include:

• Max Planck Institute for Biogeochemistry (since 2021)
• Project Group EarthNet
• Research group Atmosphere-Biosphere Coupling, Climate and Causality