Clara Yoon

Clara is an earthquake seismologist and software developer at the United States Geological Survey in Pasadena, California.  She leads the IT and software operations on the USGS side of the Southern California Seismic Network (SCSN, https://www.scsn.org), which is a collaboration between USGS and Caltech to monitor earthquake activity in southern California.

Biography

 

Education

2018                Ph.D. Geophysics, Stanford University

                        Thesis: A FAST Data Mining Approach for Similar Earthquake Detection

2015                M.S. Geophysics, Stanford University

2006                B.S. Physics, University of California Los Angeles

 

Professional Experience

2018 - present    Supervisory Geophysicist, U.S. Geological Survey, Pasadena, CA

2012 - 2018       Graduate Student Researcher, Department of Geophysics, Stanford University, Stanford, CA

2006 - 2012       Staff Scientist, Areté Associates, Northridge, CA

 

Current Projects

USGS lead role in development, maintenance, and operation of real-time earthquake monitoring software in the Southern California Seismic Network (SCSN), in collaboration with Caltech Seismo Lab

Product planning and requirements development for the next-generation Earthquake Notification Service (ENS), which sends customized real-time email and text earthquake notifications to over 400,000 users

Planning and requirements development for the next-generation ANSS Quake Monitoring Software (AQMS) used in regional seismic networks

Software maintenance, testing, documentation, and user support for the AQMS Jiggle GUI, an application for human review of earthquake waveforms, locations, and magnitudes

Testing machine learning algorithms in operational earthquake monitoring software

Planning, coordination, and support for real-time ground shaking intensity (ShakeMap) products for southern California earthquakes

Promoting software development best practices: version control, git workflow, coding standards, unit tests, integration tests, issue tracking, code review, documentation

Management, supervision, and hiring for local IT team in Pasadena

 

Current Interests

Southern California earthquake monitoring, seismicity analysis, and hazards

What new insights about earthquakes can be extracted from the application of data mining and machine learning techniques to large seismological and geophysical data sets?

How do earthquakes start, what can trigger earthquakes, how do earthquakes stop, and why do some earthquakes grow large when most do not?

How can software development best practices, open data repositories, cloud computing, and automated workflows improve transparency, reproducibility, collaboration, and dissemination of computational earthquake science research?

 

Past Projects (Research)

Developed Fingerprint And Similarity Thresholding (FAST), an unsupervised algorithm to search for earthquakes with similar waveforms in continuous seismic data sets, with durations ranging from 1 day to 11 years

Identified microearthquake clusters induced by hydraulic fracturing and deep wastewater injection in Guy-Greenbrier, Arkansas

Detected, located, and computed source parameters for foreshocks of the 1999 Mw 7.1 Hector Mine, California earthquake, and determined that foreshocks and mainshock were triggered by a cascade of stress transfer

Automatically detected and picked phases on aftershock waveforms of the 2008 Wenchuan earthquake for the SeismOlympics data science competition

Conducted multi-year InSAR time series analysis to estimate surface deformation from deep wastewater injection near Oklahoma City during 2011-2014, for the Stanford Center for Induced and Triggered Seismicity

 

Past Projects (Software Development)

Developed, tested, and documented open-source FAST application (Python/C++ on Linux clusters) for unsupervised large-scale similar earthquake detection: https://github.com/stanford-futuredata/FAST

Developed scientific software for remote sensing systems: simulation and modeling, data analysis, algorithm development, software implementation (C++, Fortran 90), software testing, documentation.  Projects involved computational geometry, synthetic aperture radar, interpolation, optical image processing, noise reduction, signal processing.

 

Publications

Hauksson, E., C. Yoon, E. Yu, J. R. Andrews, M. Alvarez, R. Bhadha, and V. Thomas (2020).  Caltech/USGS Southern California Seismic Network (SCSN) and Southern California Earthquake Data Center (SCEDC): Data Availability for the 2019 Ridgecrest Sequence, Seismological Research Letters, https://doi.org/10.1785/0220190290.

Yoon, C. E., K. J. Bergen, K. Rong, H. Elezabi, W. L. Ellsworth, G. C. Beroza, P. Bailis, P. Levis (2019). Unsupervised Large-Scale Search for Similar Earthquake Signals, Bulletin of the Seismological Society of America, 109, 4, 1451-1468, https://doi.org/10.1785/0120190006.

Yoon, C. E., N. Yoshimitsu, W. L. Ellsworth, and G. C. Beroza (2019). Foreshocks and Mainshock Nucleation of the 1999 Mw 7.1 Hector Mine, California, Earthquake, Journal of Geophysical Research – Solid Earth, 124, 1569-1582, https://doi.org/10.1029/2018JB016383.

Rong, K., C. E. Yoon, K. J. Bergen, H. Elezabi, P. Bailis, P. Levis, and G. C. Beroza (2018). Locality-Sensitive Hashing for Earthquake Detection: A Case Study Scaling Data-Driven Science, Proceedings of the VLDB Endowment, 11, 1674-1687, https://doi.org/10.14778/3236187.3236214.

Yoon, C. E., Y. Huang, W. L. Ellsworth, and G. C. Beroza (2017). Seismicity During the Initial Stages of the Guy-Greenbrier, Arkansas, Earthquake Sequence, Journal of Geophysical Research – Solid Earth, 122, https://doi.org/10.1002/2017JB014946.

Bergen, K., C. Yoon, and G. C. Beroza (2016). Scalable Similarity Search in Seismology: A New Approach to Large-Scale Earthquake Detection, Proceedings of the 9th International Conference on Similarity Search and Applications, 301-308, https://doi.org/10.1007/978-3-319-46759-7_23.

Yoon, C. E., O. O’Reilly, K. J. Bergen, and G. C. Beroza (2015). Earthquake detection through computationally efficient similarity search, Science Advances, 1, e1501057, https://doi.org/10.1126/sciadv.1501057.

 

Selected Presentations

A FAST Data-Mining Approach for Similar Earthquake Detection, 2018 SSA Meeting (invited), Miami, Florida.

Big data analytics for finding small earthquakes, UC Santa Cruz IGPP Seminar, January 2018.

Efficient blind search for similar-waveform earthquakes in years of continuous seismic data, 2017 AGU Meeting (invited), New Orleans, Louisiana, Abstract S21E-01.

Earthquake Detection Through Computationally Efficient Similarity Search (with K. Bergen), U.S. Geological Survey Earthquake Science Center Seminar, Menlo Park, CA, August 2015, https://earthquake.usgs.gov/contactus/menlo/seminars/999.

 

Professional Activities

Reviewer for Journal of Geophysical Research – Solid Earth (2019)

Reviewer for Seismological Research Letters (2019)

Proposal reviewer for National Science Foundation - Earth Sciences (2019)