Dapeng Feng
Dapeng Feng will join the Jackson School as an assistant professor in January 2026 following his postdoc at Stanford University. His research focuses on studying the terrestrial water cycle and its interactions with climate and ecosystems by integrating physical models, AI, and multi-source Earth observations. Dapeng is the major developer of the widely used differentiable hydrologic modeling framework to unify physical models and machine learning. Specifically, his group works on 1) regional to continental and global scale hydrologic modeling; 2) the interactions of water and ecosystems across scales; 3) microwave remote sensing of vegetation water and model-data integration; 4) the impacts of human activities on hydrologic and land surface processes.
Prospective graduate students/postdoc: Dapengs group is looking for highly motivated PhD students and postdoc to start in Fall 2026. If you are interested in the research topics above, please feel free to check this advertisement and contact Dapeng to apply.
Areas of Expertise
Terrestrial Water Cycle; Large-scale Hydrologic Modeling; Ecosystem-Water interactions; Hybrid AI-Physics modeling; Remote Sensing of Hydrology; Climate Change Impacts;