Dr. Weiqiang Zhu

Biography

Weiqiang Zhu's research focuses on understanding earthquake physics by applying cutting-edge artificial intelligence and scientific computing methods to gain new insights from large seismic datasets. His work in Machine Learning and Deep Learning is centered on the discovery of geophysical signals, applying deep learning techniques to detect hidden earthquake signals within large seismic datasets. This research aims to improve the understanding of complex earthquake sequences and fault zone structures. Zhu also leverages cloud computing for large-scale data mining to develop high-resolution earthquake catalogs and study mechanisms of earthquakes, geophysical processes, subsurface fluid migration, volcanic unrest, and induced seismicity. Furthermore, his studies involve earthquake simulation and seismic inversion, through which he examines multiphysics couplings in fault zones related to fluid, permeability, friction, and mechanical properties. By employing automatic differentiation, he seeks to enhance geophysical inversion, constraining key physical parameters of earthquake sources and the Earth’s interior structures.

Research Interests