TEAM – Max Planck Institute for Biogeochemistry (MPI-BGC): USMILE Host Institution

Prof Markus Reichstein

Prof. Markus Reichstein

  • Affiliation: MPI-BGC
  • Director of the Biogeochemical Integration Department at the Max-Planck Institute for Biogeochemistry and Professor for Global Geoecology at the University of Jena – WP1-4
  • USMILE co-PI
  • Personal webpage

Bernhard Ahrens*

  • Affiliation: MPI-BGC
  • Scientist – WP2
  • Hybrid modeling of soil processes ranging from radiocarbon to heterotrophic respiration.
  • Techniques: universal differential equations and physics-informed neural networks.
  • Personal webpage

Lazaro Alonso Silva

  • Affiliation: MPI-BGC
  • Research Scientist
  • Model efficiencies, neural networks, LSTMs, transformers. Hybrid modelling. Visual analytics.
  • Personal webpage

Zavud Baghirov

  • Affiliation: MPI-BGC
  • PhD Researcher
  • Combining deep learning models with physical models using different Earth observation data to develop a global model of (coupled) water and carbon cycles. Quantifying the uncertainties in hybrid modelling.

Dr. Ana Bastos*

  • Affiliation: MPI-BGC
  • Group leader – WP3
  • Climate extreme impacts and memory effects.
  • Personal webpage

Vitus Benson

  • Affiliation: MPI-BGC
  • Partial associate (pre-doctoral) – WP3
  • Spatio-temporal prediction of localized impacts to extreme weather.
  • Personal webpage

Dr. Nuno Carvalhais*

  • Affiliation: MPI-BGC
  • Group leader of the Model-Data Integration research group of the Department Biogeochemical Integration.
  • Terrestrial ecosystems; model-data integration; hybrid modeling.
  • Personal webpage

Dr. Gregory Duveiller

  • Affiliation: MPI-BGC
  • Research Scientist -WP1 and WP2
  • Investigating land-climate interactions based on satellite remote sensing.
  • Personal webpage

Reda ElGhawi

  • Affiliation: MPI-BGC
  • PhD Researcher – WP3
  • Hybrid modeling approaches to land-surface modeling; through the integration of deep learning techniques and process-based models in the framework of Earth system models.
  • Personal webpage

Johannes Gensheimer

  • Affiliation: MPI-BGC
  • PhD Researcher
  • Analysing the carbon land-atmosphere interaction based on data science, hybrid modelling, and machine learning with remote sensing data.
  • Personal webpage

Basil Kraft

  • Affiliation: MPI-BGC
  • PhD Researcher – WP1 / WP2 (TBD)
  • Hybrid modeling, using novel deep learning approaches for modeling of ecosystem fluxes (TBD).
  • Personal webpage

Guohua Liu

  • Affiliation: MPI-BGC
  • Postdoctoral Researcher
  • Hybrid modelling of vegetation phenology.
  • Personal webpage

Christian Reimers

  • Affiliation: MPI-BGC
  • Research Scientist – WP2 and WP3
  • Interpretable deep learning, causal modeling
  • Personal webpage

Albrecht Schall

  • Affiliation: MPI-BGC
  • PhD Researcher – WP3
  • Deep Learning based climate extremes and impact detection and anticipation.
  • (Uncertainty-aware) generative models.
  • Personal webpage

Feng Tao

  • Affiliation: MPI-BGC
  • PhD Researcher
  • Understanding dynamics of the global soil carbon cycle and its underlying mechanisms using ecological modeling, data assimilation, and machine learning techniques.
  • Personal webpage

Samuel Upton

  • Affiliation: MPI-BGC
  • PhD Researcher
  • Estimation of ecosystem CO2 fluxes constrained by ecosystem and atmospheric observations.
  • Personal webpage

Dr. Alexander Winkler

  • Affiliation: MPI-BGC
  • Postdoctoral Researcher – WP2 and WP4
  • Linking mechanistic models and observational data: Integration of data-driven approaches in Earth system models, specifically hybrid-modeling of land-atmosphere interactions (WP2), and constraining multi-model estimates of key entities in the Earth system using observations (i.e. Emergent Constraints, WP4).
  • Personal webpage

Xin Yu

  • Affiliation: MPI-BGC
  • PhD Researcher – WP3
  • Legacy effects of extreme events on ecosystem carbon-cycle.
  • Personal webpage

* indicates partial affiliation to USMILE.