Deep Learning for Earthquake Aftershock Patterns with Phoebe DeVries & Brendan Meade - #311

Today we are joined by Phoebe DeVries, Postdoctoral Fellow in the Department of Earth and Planetary Sciences at Harvard and assistant faculty at the University of Connecticut and Brendan Meade, Professor of Earth and Planetary Sciences and affiliate faculty in computers sciences at Harvard. In this episode, we discuss:

Phoebe and Brendan’s work is focused on discovering as much as possible about earthquakes before they happen, and through measuring how the earth’s surface moves, predicting future movement location Their recent paper, ‘Deep learning of aftershock patterns following large earthquakes’, and  The preliminary steps that guided them to using machine learning in the earth sciences Their current research involving calculating stress changes in the crust and upper mantle after a large earthquake and using a neural network to map those changes to predict aftershock locations The complex systems that encompass earth science studies, including the approaches, challenges, surprises, and results that come with incorporating machine learning models and data sets into a new field of study

The complete show notes for this episode can be found at twimlai.com/talk/311.