- Tech F493
My research focuses on improving earthquake shaking forecasts. Although shaking forecasts are one of seismology’s most important public contributions, they present major intellectual challenges. Seismic hazard maps, used in developing codes that specify building design, seek to forecast future shaking at certain probabilities over decades. Until recently, seismologists knew surprisingly little about how well hazard maps predict the shaking that actually occurs. My group uses “hindcasting” by compiling data over long periods to assess map forecasts and realistically predict key aspects of future shaking. From these assessments, we've found that the maps forecast higher shaking than what has been observed in historical datasets. My PhD work is focusing on determining why this overprediction occurs and how we can minimize it, thus making the maps as accurate as possible. To do this, I'm investigating the role of input models to the maps, conversion equations used during map assessment, and statistical practices to develop the maps.
- Honorable Mention, NSF Graduate Research Fellowship Program, 2020
- Outstanding Student Presentation Award, American Geophysical Union, 2019