Max Planck Gesellschaft
Reda ElGhawi

PhD student in the

room: C1.016 (tower)
phone: +49 3641 576228
email: relghawi(at)

Research interests | Current Research | Past Research | Publications

Research Interest:

  • 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

Current Research:

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.


ElGhawi, R., Pekhazis, K., & Doummar, J. (2021). Multi-regression analysis between stable isotope composition and hydrochemical parameters in karst springs to provide insights into groundwater origin and subsurface processes: regional application to Lebanon. Environmental Earth Sciences, 80(6), 1-21.

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