Machine Learning in Seismology: Challenges and Solutions

Today we’re joined by Karianne Bergen, an assistant professor at Brown University. In our conversation with Karianne, we explore her work at the intersection of earthquake seismology and machine learning, where she’s working on interpretable data classification for seismology. We discuss some of the challenges that present themselves when trying to solve this problem, and the state of applying machine learning to seismological events and earth sciences. Karianne also shares her thoughts on the different relationships that computer scientists and natural scientists have with machine learning, and how to bridge that gap to create tools that work broadly for all scientists.

The complete show notes for this episode can be found at twimlai.com/go/554