Deep Learning for Earthquake Aftershock Patterns with Phoebe DeVries & Brendan Meade - #311
Published:Oct 25, 2019 17:35
•1 min read
•Practical AI
Analysis
This article from Practical AI highlights the research of Phoebe DeVries and Brendan Meade on using deep learning to predict earthquake aftershock patterns. Their work, focusing on understanding earthquakes and predicting future movement, is crucial for improving preparedness. The article mentions their paper, which likely details the specific deep learning methods and data used. The focus on predicting aftershocks is particularly important for hazard assessment and risk mitigation following a major earthquake. The interview format suggests an accessible explanation of complex scientific concepts.
Key Takeaways
- •Deep learning is being used to analyze earthquake aftershock patterns.
- •The research aims to predict future earthquake movement.
- •The work is conducted by researchers at Harvard University.
Reference
“Phoebe and Brendan’s work is focused on discovering as much as possible about earthquakes before they happen, and by measuring how the earth’s surface moves, predicting future movement location.”