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| Name |
Beroza, Gregory C. |
| Location
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Stanford University |
| Primary Field
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Geophysics |
| Secondary Field
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Geology |
 Election Citation
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Beroza's work has advanced fault-slip imaging, informed models of earthquake dynamics and predictability, and pioneered machine-learning methods in seismology. |
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Research Interests
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Greg Beroza's research focus is on using records of ground motion known as seismograms to develop a clearer understanding of earthquake processes. His group has worked on fast, slow, intermediate-depth, and human-induced earthquakes. They have developed a framework for understanding the properties of a distinct family of slow earthquakes and went on to elucidate the shear character of low frequency earthquakes and tectonic tremor. He has developed open-source data-mining and machine-learning methods for improved small earthquake detection and characterization. Application of these precision seismology techniques to tectonic earthquakes, induced earthquakes, and magmatic systems has resulted in greatly improved completeness of seismicity catalogs and a clearer illumination the 3D geometry of complex fault systems. His research group has also used ambient field measurements to constrain both elastic and anelastic Earth structure, and to predict directly the strength and variability of earthquake strong ground motion. |
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