My research is within the domain of observational seismology. The study subjects include but not limited to fault zone structures, earthquake evolution, and generic seismic events (both natural and anthropogenic). The tools include cutting-edge instruments (e.g. nodal sensors) and data-mining techniques (e.g. machine learning algorithms).
Word Cloud of My Publications
Research Summary
My research in observational seismology uses voluminous seismic data to understand earthquake processes and the Earth's interior. As a data-driven science, seismology advances with increasing amount of seismic data, improved computational and experimental tools. My Ph.D. thesis has focused on crustal anisotropy using split shear waves. I also has investigated the use of Large-N arrays and developed novel techniques for high-resolution detection of general seismic events. Now, as a postdoc at Caltech, I am striving to introduce machine learning into seismology, particularly into earthquake early warning systems. Generally, I am excited to explore broad interdisciplinary studies between seismology and other Science/Engineering branches, which I would like to coin as Seismology+X.
1. Machine Learning & Earthquake Early Warning
2. Large-N/DAS Arrays & Microseismic Detection
3. Fault Zone Structures & Crustal Anisotropy