Research
My work bridges the gap between traditional seismology, environmental science, and modern computational methods.
Soil Hydrodynamics & Farming
Investigating how farming practices impact soil hydrodynamics using seismic noise. This novel approach, termed "Agroseismology," allows for non-invasive monitoring of soil properties and water content changes over time, providing critical insights for sustainable agriculture.
- Seismic noise interferometry
- Soil moisture monitoring
- Sustainable agricultural practices
AI for Earthquake Detection
Developing advanced machine learning models to improve earthquake detection and analysis. By using masked auto-encoders and other deep learning techniques, we can denoise distributed acoustic sensing (DAS) data and identify deep earthquake ruptures that were previously undetectable.
- Masked Auto-Encoders (MAE)
- DAS data denoising
- Deep rupture observation
Earthquake Physics
Investigating the fundamental physics of earthquake rupture, stress transfer, and fault mechanics. My work combines seismic waveform analysis, geodetic data, and numerical modeling to understand how earthquakes initiate, propagate, and interact with complex fault geometries.
- Rupture dynamics and stress transfer
- Waveform inversion and source characterization
- Fault geometry and pore fluid effects
