My work focuses on the application of data science and machine learning techniques to earthquake monitoring and geophysical forecasting. A significant focus of my research is the processing of large seismic networks to accurately detect, locate, and characterize earthquakes. We often employ graph-based and graph neural network-driven techniques to handle time-varying and spatially irregular seismic networks. Understanding and forecasting tectonic and volcanic processes through these data-driven techniques is a key interest. Additionally, improving methods for efficient neural-surrogate emulation of the relevant PDEs behind these physical processes is an important area of study.