Thread: AGU Session S011: Applications of Data Science and Machine Learning in Seismology

Dear Colleagues,

Please consider submitting your work to our session on Applications of Data Science and Machine Learning in Seismology, in the Seismology Section of the 2017 AGU Fall meeting to be held December 11-15 in New Orleans. Note the deadline for abstract submission is Wednesday, August 2.

Session ID: 26176
Session Title: S011. Applications of Data Science and Machine Learning in Seismology
Session Description: We currently are experiencing a dramatic increase in the volume, variety, and velocity of data in seismology. Methods and tools from data science and machine learning enable characterization of different types of signals, noise reduction, event detection, phase identification, seismic source characterization, inference of Earth's seismic structure, and novel visualizations. With all the data available to researchers and practitioners in the field of seismology and advances in computational systems, there are great opportunities for data science and machine learning algorithms to extract meaningful insights for reducing earthquake hazards, understanding plate tectonics, earthquakes and earth structures, and improving the detection and limiting the proliferation of nuclear weapons. We encourage contributions on the methods and results of combining techniques and tools from data science and machine learning with seismology.

You can submit your abstract here: https://agu.confex.com/agu/fm17/preliminaryview.cgi/Session26176

We look forward to an exciting session with your participation!

Best,

Timothy Draelos, Sandia National Laboratories, Albuquerque, NM, United States
Qingkai Kong, University of California Berkeley, Berkeley, CA, United States