Data-driven research


TLDR bio: I solve scientific problems using data, computer programs, and ML.

Technical bio: I utilize and develop quantitative techniques and computational tools to derive insights from data and models. In a broad context, I am interested in solving data-driven problems with software and sensors. My past research comprises:

  • constraining the stress state in Earth’s crust at enigmatic depths by inverting slow-earthquake slip vectors
  • inferring landslide mechanics via microseismic events from machine learning-based automated time series signal detection and association techniques, event locations, and source analysis
  • constraining vertical land motion in coastal Washington via multi-methods interpolation
  • inventing a hardware interface with nodal seismic sensors to improve sensor alignment
  • automating object detection, classification, and shape parametrization of volcanics images via computer vision techniques

Latest Blog Post

Optimizing componentry of volcanic particles with computer vision.

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Research Summary

Explore my past and current research in seismology and computational science.

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Earthquake Seismology at University of Oregon

Researching seismotectonics, fault mechanics, and crustal deformation via observation and modeling.

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