Ryan Tam is a Data Scientist and Software Developer for Caltech's Seismological Laboratory. He develops software workflows that utilize machine algorithms to make earthquake predictions from waveform data. He also has a background in computer vision and biomedical engineering, having used deep learning for disease diagnostics. Ryan's interests include cloud computing, deep learning, software engineering, containers, and infrastructure as code.

Presentations

22x

AI, Cloud Computing, and Software Engineering Concepts in Seismology

The current state of earthquake monitoring systems utilize standard algorithms that process seismic data and run software on local servers. While this system has proven effective for twenty-plus years, it is a dated system in need of modernization. The Southern California Seismic Network is exploring ways to generate earthquake products with modern software technologies such as cloud-native services, AI-powered models, serverless computing, containers, and infrastructure as code. The SCSN aims to develop a system that other networks might be motivated to adopt.

 

See Presentation