Extracting important and relevant physics from data and developing models with predictive power will be a significant task in the future of Earth sciences. Many of my observation-oriented projects share the theme of utilizing a Bayesian probabilistic inference framework (analytical and numerical sampling approaches) with an emphasis on uncertainty quantification of observations and physical modeling, along with its impact on our predictions.
The second, complementary part of my research involves developing cross-scale computational models with detailed physics and predictive powers to understand earthquakes, tsunamis, or slow slip. We are also interested in the verification and validation of these complex models. I take a special interest in the synergy of developing inverse and forward modeling in geophysical problems to eventually improve observation-drive, physics-based inference about the future behavior of our Earth.