Research Interest
Hydrological and Water Resources Modeling
Hydrological Extreme Events
Machine Learning and AI for Hydrology
Education
Ph.D. in Civil and Environmental Engineering, with a minor in Statistics, University of Illinois Urbana-Champaign, 2024
M.S. in Civil and Environmental Engineering, University of Illinois Urbana-Champaign, 2020
B.E. in Hydraulic Engineering, Tsinghua University, 2018
Research Experience and Direction
My research focuses on integrated hydrological and water resources modeling, where I develop and couple models for various interacting processes and components within hydrological systems. I apply these integrated models to study extreme events and assess their associated natural disasters. My research efforts have included:
Reservoir operation modeling: developing generalized data-driven empirical reservoir operation rules to represent human water management in large-scale hydrological and water resources modeling.
Integrated and large-scale hydrological modeling: developing models for different processes within hydrological systems, including data-driven reservoir operation model, frozen ground model, and scaling-law based routing model, using both physical-based and data-driven approaches.
Extreme events modeling: developing and applying hydrological models with flood innudation mapping models to study flood risks from regional to continental scale.Â
Technical Skills
Programming: Python, R, C, Fortran, Matlab, Bash scripting.
Machine learning/AI: Scikit-learn, PyTorch.
HPC: Extensive expriences with campus clusters and supercomputers.