© R.ElGhawi/BGC
Reda El Ghawi
Department Biogeochemical Integration (BGI)
Project group Atmosphere-Biosphere Coupling, Climate and Causality
Intern. Max Planck Research School for Global Biogeochemical Cycles (IMPRS-gBGC)
USMILE
Project group Atmosphere-Biosphere Coupling, Climate and Causality
Intern. Max Planck Research School for Global Biogeochemical Cycles (IMPRS-gBGC)
USMILE
Main Focus
My current research focuses on the integration of machine learning with land-surface modelling, ie. hybrid modelling to characterize transpiration and photosynthesis. (Biological) Processes defined by semi-empirical properties are modelled with machine learning techniques that will be integrated into the land-surface model JSBACH, allowing for the conservation of physical laws while enabling the exploitation of complex relationships to be learnt with higher accuracy.
- Understanding and modelling the Earth System with machine learning techniques
- Deep learning approaches for modelling processes described by semi-empirical formulations
- Hybrid modelling approaches to land-surface models