My research typically pertains to computational seismology. In the context of University of Utah Seismograph Stations that typically means developing the business logic to deliver data products of higher-quality more consistently and more expediently. This typically involves packaging theoretical and practical seismological principles into an automatic decision making framework.
To enhance feature extraction for machine learning algorithms and expedite routine seismic processing I am perpetually extending a library for real-time processing and post-processing of seismic signals. RTSeis is available here.
Making picks on a seismogram is tedious and in some instances quite ambiguous. A way around this is to leverage the network's sensitivity and perform pickless location using an interferometric technique. XCLoc is available here.
Quite frequently in seismology we have to determine how long it took a seismic signal to make its way from the source to a receiver. One way to do that is by solving a high-frequency approximation to the wave equation. An eikonal solver for use in strongly heterogeneous media is available here.
GEO 5920/6920: Statistical Methods Applied to Earthquake Seismology. This is a machine learning class which is specialized for regional network seismology.
Periodically UUSS makes available undergraduate research positions. Please email me to learn about current undergraduate student research opportunities.
My CV is available here here.