School of Earth, Energy and Environmental Sciences
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Ph.D. Student in Geophysics
Current Research and Scholarly InterestsThe most destructive tsunamis are generated by earthquakes, posing hazard to coastlines around the world. Open questions about these events are, how are they generated, what parameters will cause the most destructive waves, and how do we interpret existing seafloor data to create tsunami and earthquake early warning? To answer these questions, computer simulations (modeling) have been an effective method to study past events and assess a region's potential hazard. Many modelers use an approximate approach for modeling how earthquakes generate tsunamis, but recent events have shown assumptions in these approaches do not hold in all cases. Since these models do not fully describe the physics, they are less effective in predicting future hazards.
A more rigorous full-physics method has been developed by a previous group member that does not approximate tsunami generation, creating a more realistic model of earth/ocean interactions. This full-physics method has only been developed in 2D; however, a 3D model is needed to allow for comparison to real-world data. In collaboration with the University of Munich, I am currently incorporating the full-physics method into the open-source 3D earthquake software. This software will be the first 3D full-physics model for earthquake tsunamigenesis, providing greater insight into tsunami physics and valuable information for tsunami early warning.
In addition to my thesis work, I have focused on two other projects to study hazards. I have completed my starter project studying frictional effects on earthquake behavior and completed my second project working with the US Geological Survey on improving ground motion prediction equations used in the earthquake early warning systems.
Ph.D. Student in Geophysics
BioAakash Ahamed (BS, with honors, Franklin and Marshall College; MSc, Boston College; PhD Candidate, Stanford University) is a hydrologist developing scientific methods for satellite and airborne remote sensing measurements with applications to water resources, natural hazards, and agricultural systems. As a PhD Candidate in the Department of Geophysics, his current doctoral project focuses on modeling, monitoring, and forecasting key hydrologic components of the Central Valley Aquifer System in California using techniques in data assimilation and machine learning. Aakash previously worked as a support scientist in the Hydrological Sciences Lab at NASA Goddard Space Flight Center, where he constructed satellite-based models of flood and landslide hazards. He has also developed remote sensing analyses and software at Ceres Imaging, a successful precision agriculture start up based in Silicon Valley, and interned as a GIS analyst at the World Wildlife Fund for Nature in Washington, DC.