Machine Learning for Hydrological and Earth Systems

Dr. Shijie Jiang

The project group was newly founded in August 2023. 

The Machine Learning for Hydrological and Earth Systems (ML4HES) group, led by Dr. Shijie Jiang and funded by the Carl Zeiss Foundation is part of the ELLIS Unit Jena and affiliated with the Max Planck Institute for Biogeochemistry.


In the face of increasing environmental and climatic pressures, understanding the variability and causality of water, energy, and carbon cycles across spatial and temporal scales is critical for effective resource management, ecosystem sustainability, extreme event mitigation, and climate resilience strategies. Our research emphasizes the integration of data and domain knowledge with hybrid and explainable machine learning methods to improve the understanding of the interactions of climate, water, and ecosystems. Our ultimate goal is to both develop new tools and advance the Earth science that guides sustainable development and risk adaptation strategies under changing conditions.


Research Interests

  • Terrestrial ecohydrological processes and interactions at different scales
  • Integration of physics and data with hybrid and explainable AI
  • Coupling and feedback mechanisms between water, energy, and carbon cycles
  • Predictability, attribution, and impacts of climate extremes
  • Hydroclimatology, climate change impacts, and human influences


Shijie Jiang
Project Leader
  • +49 3641 57-8901
ITP B3.18
MPG PublicationsWebpage at ELLIS Unit Jena
Georgios Blougouras
Doctoral Researcher
  • +49 3641 57-8918
ITP B3.24
ELLIS Unit Jena Page Google Scholar Profile
Feini Huang
  • +49 3641 57-8909
ITP B3.28
Google Scholar Profile ResearchGate
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