We develop novel GPU-enabled high-performance computing frameworks, reduced-order models, and data assimilation techniques to understand and predict complex Earth system processes and natural hazards——including landslides, ice sheet dynamics, flooding, wildfire, and more. Our research places particular emphasis on thermal-hydro-mechanical (THM) coupling in geosystems, especially under extreme environmental conditions.
Natural Hazards
Landslides
Collapse of granular column
Compound Flooding Modeling
Relavant Papers:
- Feng, D., Tan, Z., He, Q. (2023) Physics-informed neural networks of the Saint-Venant equations for flood modeling. Water Resources Research.
Glaciers
Ice Sheet Modeling
- He, Q., Perego, M., Howard, A. A., Karniadakis, G. E., & Stinis, P. (2023). A hybrid deep neural operator/finite element method for ice-sheet modeling. Journal of Computational Physics, 492, 112428.