Markus Reichstein

Prof. Dr. Markus Reichstein serves as Director of the Department of Biogeochemical Integration at the Max Planck Institute for Biogeochemistry and Professor of Global Geoecology at Friedrich Schiller University Jena. He is Founding Director of both the Michael Stifel Center Jena for Data-Driven and Simulation Sciences and the ELLIS Unit Jena, positioning him at the forefront of integrating artificial intelligence with Earth system science.

His research focuses on understanding ecosystem responses to climate variability from an Earth system perspective, with particular emphasis on climate extremes and ecosystem resilience. Prof. Reichstein combines artificial intelligence with systems modeling approaches to analyze experimental data, ground-based observations, and satellite Earth observations across multiple spatial scales.

His recent publication record shows a strong emphasis on applying machine learning to biogeochemical processes, with numerous 2025 publications addressing carbon cycle modeling, soil moisture prediction, drought impacts, and AI applications for climate risk assessment. These works demonstrate his interdisciplinary approach that bridges ecology, climate science, and computational methods.

• Piers J. Sellers Mid-Career Award from the American Geophysical Union (2018)
• ERC Synergy Grant (2019)
• Gottfried Wilhelm Leibniz Prize (2020)
• AGU Fellow (2025)

As department director and through his various leadership roles, Prof. Reichstein oversees substantial research funding and mentorship opportunities. His department regularly welcomes new researchers and students, fostering an environment of international collaboration. The integration of the Michael Stifel Center and ELLIS Unit with his department creates unique opportunities for students interested in the intersection of AI and environmental science.

The Department of Biogeochemical Integration, under Prof. Reichstein's leadership, serves as a hub for innovative research on Earth system processes, combining traditional ecological approaches with cutting-edge computational methods to address pressing climate challenges.