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Michelle Guy

I architect, manage, and build highly specialized state-of-the-art scientific software systems. These systems are one of a kind and serve to bring the unique science of the GHSC into real-time operations and produce products for worldwide consumption by scientific communities, emergency responders, government agencies and the general public.

Funding                  

  • Crowd-Sourced Earthquake Detections Integrated with Instrumental Seismic Processing; PI; April 2016;  Community for Data Integration, USGS; http://bit.ly/2gxWsX0
  • Characterization of Earthquake Damage and Effects Using Social-Media Data; Co-PI; April 2014; Community for Data Integration, USGS

Publications

  • Guy, Michelle, Patton, John, Fee, J.M., Hearne, Mike, Martinez, E.M., Ketchum, D., Worden, C.B., Quitoriano, Vince, Hunter, E.J., Smoczyk, G.M., and Schwarz, Stan, 2015, National Earthquake Information Center systems overview and integration: U.S. Geological Survey Open-File Report 2015–1120, 25 p., http://dx.doi.org/10.3133/ofr20151120.
  • Patton, J.M., Ketchum, D.C., and Guy, M.R., 2015, An overview of the National Earthquake Information Center acquisition software system, Edge/Continuous Waveform Buffer: U.S. Geological Survey Open-File Report 2015–1174, 10 p., http://dx.doi.org/10.3133/ofr20151174.
  • Madison L. Langseth, Michelle Y. Chang, Jennifer Carlino, Daniella D. Birch, Joshua Bradley, R. Sky Bristol, Craig Conzelmann, Robert H. Diehl, Paul Earle, Laura E. Ellison, Anthony L. Everette, Pam Fuller, Janice M. Gordon, David L. Govoni, Michelle R. Guy, Heather S. Henkel, Vivian B. Hutchison, Tim Kern, Frances L. Lightsom, Joseph W. Long, Ryan Longhenry, Todd M. Preston, Stan Smith, Roland J. Viger, Katherine Wesenberg, Eric Wood. (July 2015). “Community for Data Integration 2014 Annual Report”. IPDS number IP-066330.
  • Michelle Guy. Paul Earle, Scott Horvath, Jessica Turner, Douglas Bausch, Greg Smoczyk; Association of Computing Machinery (ACM) Significant Interest Group conference on Knowledge Discovery and Data Mining (SIGKDD) workshop on Learning about Emergencies from Social Media (LESI) August 2014: “Social Media Based Earthquake Detection and Characterization”; https://sites.google.com/site/kddlesi2014/program/papers;   
  • Earle, P.S., D.C. Bowden, and M. Guy (2011) Twitter earthquake detection: earthquake monitoring in a social world. Annals of Geophysics, 54(6), 708-715.                                                         
  • Guy, M., P. Earle, C. Ostrum, K. Gruchalla and S. Horvath (2010) Integration and dissemination of citizen reported and seismically derived earthquake information via social network technologies. Advances in Intelligent Data Analysis IX Lecture Notes in Computer Science, 6065/2010, 42-53.                  &nb

Science and Products

link
USGS science for a changing world logo

Crowd-Sourced Earthquake Detections Integrated into Seismic Processing

The goal of this project is to improve the USGS National Earthquake Information Center’s (NEIC) earthquake detection capabilities through direct integration of crowd-sourced earthquake detections with traditional, instrument-based seismic processing. During the past 6 years, the NEIC has run a crowd-sourced system, called Tweet Earthquake Dispatch (TED), which rapidly detects earthquakes worldwide...
By
Community for Data Integration (CDI)
link

Crowd-Sourced Earthquake Detections Integrated into Seismic Processing

The goal of this project is to improve the USGS National Earthquake Information Center’s (NEIC) earthquake detection capabilities through direct integration of crowd-sourced earthquake detections with traditional, instrument-based seismic processing. During the past 6 years, the NEIC has run a crowd-sourced system, called Tweet Earthquake Dispatch (TED), which rapidly detects earthquakes worldwide...
Learn More
link
USGS science for a changing world logo

Characterization of Earthquake Damage and Effects Using Social Media Data

People in the locality of earthquakes are publishing anecdotal information about the shaking within seconds of their occurrences via social network technologies, such as Twitter. In contrast, depending on the size and location of the earthquake, scientific alerts can take between two to twenty minutes to publish. The goals of this project are to assess earthquake damage and effects information, as
By
Community for Data Integration (CDI)
link

Characterization of Earthquake Damage and Effects Using Social Media Data

People in the locality of earthquakes are publishing anecdotal information about the shaking within seconds of their occurrences via social network technologies, such as Twitter. In contrast, depending on the size and location of the earthquake, scientific alerts can take between two to twenty minutes to publish. The goals of this project are to assess earthquake damage and effects information, as
Learn More

Seismic monitoring during crises at the NEIC in support of the ANSS

Over the past two decades, the U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) has overcome many operational challenges. These range from minor disruptions, such as power outages, to significant operational changes, including system reconfiguration to handle unique earthquake sequences and the need to handle distributed work during a pandemic. Our ability to overcome cr
By
Natural Hazards, Volcano Hazards, Geologic Hazards Science Center, Volcano Science Center

Leveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center

Machine‐learning algorithms continue to show promise in their application to seismic processing. The U.S. Geological Survey National Earthquake Information Center (NEIC) is exploring the adoption of these tools to aid in simultaneous local, regional, and global real‐time earthquake monitoring. As a first step, we describe a simple framework to incorporate deep‐learning tools into NEIC operations.
By
Natural Hazards, Geologic Hazards Science Center

GLASS3: A standalone multi-scale seismic detection associator

The automated global real-time association of phase picks into seismic sources comes with unique challenges when simultaneously monitoring at local, regional and global scales. High spatial variability in seismic station density, transitory seismic data availability, and time-varying noise characteristics of individual stations must be considered in the design of an associator that is fast and ac
By
Natural Hazards, Earthquake Hazards, Geologic Hazards Science Center

Limiting the effects of earthquakes on gravitational-wave interferometers

Ground-based gravitational wave interferometers such as the Laser Interferometer Gravitational-wave Observatory (LIGO) are susceptible to ground shaking from high-magnitude teleseismic events, which can interrupt their operation in science mode and significantly reduce their duty cycle. It can take several hours for a detector to stabilize enough to return to its nominal state for scientific obser
By
Natural Hazards, Earthquake Hazards, Geologic Hazards Science Center

Science and Products

  • Science
    link
    USGS science for a changing world logo

    Crowd-Sourced Earthquake Detections Integrated into Seismic Processing

    The goal of this project is to improve the USGS National Earthquake Information Center’s (NEIC) earthquake detection capabilities through direct integration of crowd-sourced earthquake detections with traditional, instrument-based seismic processing. During the past 6 years, the NEIC has run a crowd-sourced system, called Tweet Earthquake Dispatch (TED), which rapidly detects earthquakes worldwide...
    By
    Community for Data Integration (CDI)
    link

    Crowd-Sourced Earthquake Detections Integrated into Seismic Processing

    The goal of this project is to improve the USGS National Earthquake Information Center’s (NEIC) earthquake detection capabilities through direct integration of crowd-sourced earthquake detections with traditional, instrument-based seismic processing. During the past 6 years, the NEIC has run a crowd-sourced system, called Tweet Earthquake Dispatch (TED), which rapidly detects earthquakes worldwide...
    Learn More
    link
    USGS science for a changing world logo

    Characterization of Earthquake Damage and Effects Using Social Media Data

    People in the locality of earthquakes are publishing anecdotal information about the shaking within seconds of their occurrences via social network technologies, such as Twitter. In contrast, depending on the size and location of the earthquake, scientific alerts can take between two to twenty minutes to publish. The goals of this project are to assess earthquake damage and effects information, as
    By
    Community for Data Integration (CDI)
    link

    Characterization of Earthquake Damage and Effects Using Social Media Data

    People in the locality of earthquakes are publishing anecdotal information about the shaking within seconds of their occurrences via social network technologies, such as Twitter. In contrast, depending on the size and location of the earthquake, scientific alerts can take between two to twenty minutes to publish. The goals of this project are to assess earthquake damage and effects information, as
    Learn More
  • Publications

    Seismic monitoring during crises at the NEIC in support of the ANSS

    Over the past two decades, the U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) has overcome many operational challenges. These range from minor disruptions, such as power outages, to significant operational changes, including system reconfiguration to handle unique earthquake sequences and the need to handle distributed work during a pandemic. Our ability to overcome cr
    By
    Natural Hazards, Volcano Hazards, Geologic Hazards Science Center, Volcano Science Center

    Leveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center

    Machine‐learning algorithms continue to show promise in their application to seismic processing. The U.S. Geological Survey National Earthquake Information Center (NEIC) is exploring the adoption of these tools to aid in simultaneous local, regional, and global real‐time earthquake monitoring. As a first step, we describe a simple framework to incorporate deep‐learning tools into NEIC operations.
    By
    Natural Hazards, Geologic Hazards Science Center

    GLASS3: A standalone multi-scale seismic detection associator

    The automated global real-time association of phase picks into seismic sources comes with unique challenges when simultaneously monitoring at local, regional and global scales. High spatial variability in seismic station density, transitory seismic data availability, and time-varying noise characteristics of individual stations must be considered in the design of an associator that is fast and ac
    By
    Natural Hazards, Earthquake Hazards, Geologic Hazards Science Center

    Limiting the effects of earthquakes on gravitational-wave interferometers

    Ground-based gravitational wave interferometers such as the Laser Interferometer Gravitational-wave Observatory (LIGO) are susceptible to ground shaking from high-magnitude teleseismic events, which can interrupt their operation in science mode and significantly reduce their duty cycle. It can take several hours for a detector to stabilize enough to return to its nominal state for scientific obser
    By
    Natural Hazards, Earthquake Hazards, Geologic Hazards Science Center