Computing

I have been fortunate to gain expertise in building computational tools to ease the processing of large seismic datasets. Below are some examples of my experience!

Cloud resources for running earthquake detection workflows

With Marine Denolle’s group and collaborators at UW’s eScience Institute, I have been working to migrate our local earthquake detection workflows onto the Microsoft Azure cloud.

We have developed and documented our experience with the cloud, including timing and costs associated with scaling, in the hopes that it may be a helpful starting point for other seismic researchers.

I presented this work at SSA 2023 and we recently submitted a manuscript describing this work for publication. You can find the codes and tutorials associated with this project here.

eScience Incubator Program: Machine-learning-based detection of offshore earthquakes

In Winter 2022, I participated in the eScience Institute’s Incubator program, where I worked alongside data scientist Scott Henderson for 10 weeks to hone my python skills and build a code base for the machine-learning-based detection of offshore earthquakes.

The seminar I gave following this program is available on Youtube!