Research Bio
Weiqiang Zhu's research focuses on understanding earthquake physics and statistics by applying cutting-edge artificial intelligence and scientific computing methods to gain new insights from large seismic datasets.
Machine Learning/Deep Learning for Geophysical Signal Discovery
- Applying deep learning to detecting hidden earthquake signals from large seismic datasets to understand complex earthquake sequences and fault zone structures.
- Applying cloud computing to large-scale data mining to build high-resolution earthquake catalogs for studying earthquake mechanisms and other geophysical processes, such as subsurface fluid migration, volcanic unrest, and induced seismicity.
Earthquake Simulation and Seismic Inversion for Understanding Earthquake Physics
- Applying earthquake simulation to analyze multiphysics couplings within fault zones such as fluid, permeability, friction, and other mechanical properties.
- Applying automatic differentiation to improve geophysical inversion and constrain key physical parameters such as earthquake source parameters and the Earth’s interior structures.
Research Expertise and Interest
earthquake physics, geophysical signal discovery