Presentations
Invited Talks
Distributed acoustic sensing (DAS) and big scientific data analysis [virtual]
Distributed Acoustic Sensing Virtual Workshop and Tutorial, IRIS, Aug 2020. [ workshop website ] [ video ( + captions) ] [ slides ]
Event detection in big sensor data: Applications in earthquake seismology and beyond [virtual]
Life on Planet Earth: Above and Below Workshop, Mathematical Biosciences Institute, Ohio State University, Columbus, OH, Aug 2020. [ workshop website ] [ video ]
Big data for small earthquakes: Computational challenges in large-scale earthquake detection
Data Science Institute and Department of Computer & Information Sciences, University of Delaware, Newark, DE, March 2020. [virtual]
Faculty of Computing & Data Science, Boston University, Boston, MA, March 2020. [virtual]
Department of Electrical & Computer Engineering, University of California, Santa Barbara, CA, March 2020.
Department of Earth, Ocean & Atmospheric Sciences, University of British Columbia, Vancouver, Canada, March 2020.
Data Science Initiative and Department of Earth, Environmental & Planetary Sciences, Brown University, Providence, RI, Feb 2020.
Department of Geophysics, Colorado School of Mines, Golden, CO, Feb 2020.
Oden Institute for Computational Sciences & Engineering and Department of Statistics and Data Science, University of Texas at Austin, TX, Feb 2020.
Department of Computational Mathematics, Science & Engineering, Michigan State University, East Lansing, MI, Feb 2020.
Machine learning for data-driven discovery in solid Earth geoscience.
National Academies Committee on Seismology and Geodynamics Fall Meeting, Washington, DC, Oct 2019. [ meeting website ] [ video ]
Earthquake monitoring in the age of “big data:” Challenges and opportunities.
Women in Data Science @ Stanford Earth workshop, Stanford University, CA, Nov 2019. [ news release ]
Department of Geosciences, Princeton University, Princeton, NJ, Nov 2019.
UTIG Seminar, Institute for Geophysics, Jackson School of Geosciences, University of Texas at Austin, TX, Sept 2019. [ video ] [ slides ]
Data mining for earthquake detection: Lessons for data-driven geoscience.
Machine Learning in Solid Earth Geoscience Conference, Santa Fe, NM, March 2019. [ conference website ]
Shaking up seismology: Improving earthquake detection capabilities with locality-sensitive hashing.
"Machine Learning Ideas" Lunch, Microsoft Research New England, Cambridge, MA, March 2019.
Machine Learning in Seismology: Using AI to Improve Earthquake Monitoring.
Congressional briefing (with Z. Ross), hosted by the Seismological Society of America, Washington D.C. Feb 2019. [ SSA Policy Events ] [ abstract ]
Towards data-driven earthquake detection: Extracting weak seismic signals with locality-sensitive hashing.
Conference on Neural Information Processing Systems, Workshop on Machine Learning for Geophysical & Geochemical Signals, Montreal, Canada. Dec 2018. [ workshop website ]
Improving earthquake detection with data mining and machine learning.
IRIS Workshop: Foundations, Frontiers & Future Facilities for Seismology, Albuquerque, NM, June 2018. [ workshop website ] [ abstract ] [ slides ]
Big data for small earthquakes: a data mining approach to large-scale earthquake detection.
Department of Applied Mathematics, University of Washington, Seattle, WA, April 2019.
Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, Feb 2019.
Department of Earth, Environmental and Planetary Sciences, Brown University, Providence, RI, Oct 2018.
FISH Seminar, Earth Resources Laboratory, MIT, Cambridge, MA, Sept 2018. [ video ]
Data Science and Cyber Analytics Group, Sandia National Laboratory, Livermore, CA, Feb 2018.
Scalable Similarity Search for Earthquake Detection.
Institute of Mathematical and Computational Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, Jan 2018.
Data Mining for Microseismic Event Detection.
Society of Exploration Geophysics Annual Meeting, Workshop on Data Analytics for Geoscience, Houston, TX, Sept 2017.
FAST: Earthquake Detection using Computationally Efficient Similarity Search.
Conference Presentations and Posters
Towards robust, reliable earthquake detection with deep neural networks (iPoster / talk)
JpGu-AGU Meeting, Chiba, Japan, July 2020. [virtual]
How robust is deep learning-based earthquake detection? Insights from adversarial machine learning. (Talk)
American Geophysical Union Fall Meeting, San Francisco, CA Dec 2019.
Short Courses and workshops as a path into data science. (Talk)
American Geophysical Union Fall Meeting, Washington, D.C., Dec 2018. [ link ]
FAST: a data mining approach to large-scale earthquake detection. (Poster)
Harvard Data Science Initiative Conference, Cambridge, MA, Oct 2019.
Women in Data Science Conference, Cambridge, MA, Jan 2019.
American Geophysical Union Fall Meeting, Washington, D.C., Dec 2018. [ link ]
Extending FAST to detect over a seismic network. (Poster)
Machine Learning in Solid Earth Geoscience, Santa Fe, NM, Feb 2018.
Automatic Earthquake Detection by Active Learning. (Poster)
American Geophysical Union Fall Meeting, New Orleans, LA, Dec 2017. [ link ]
On the Use of Machine Learning for Seismic Event Detection. (Talk)
Seismological Society of America Annual Meeting, Denver, CO, April 2017. [ link ] [ student presentation award ]
Data Mining for Microseismic Event Detection. (Talk)
Society of Exploration Geophysics Annual Meeting, Workshop on Data Analytics for Geoscience, Houston, TX , Sept 2017.
Earthquake Fingerprints: Representing Earthquake Waveforms for Similarity-Based Detection. (Poster)
American Geophysical Union Fall Meeting, San Francisco, CA, Dec 2016. [ link ]
Scalable Similarity Search: A New Approach for Large-Scale Earthquake Detection. (Talk, Poster)
International Conference on Similarity Search and Applications, Tokyo, Japan, Oct 2016. [ link ]
Data Mining for Earthquake Detection using Computationally Efficient Search for Similar Seismic Signals. (Talk)
Seismological Society of America Annual Meeting, Reno, NV, April 2016. [ link ] [ slidecast ] [ student presentation award ]
Unsupervised Approaches for Post-Processing in Computationally Efficient Waveform-Similarity-Based Detection. (Poster)
American Geophysical Union Fall Meeting, San Francisco, CA, Dec 2015. [ link ] [ student paper award ]
Fingerprint and Similarity Thresholding for Computationally Efficient Earthquake Detection. (Poster)
Southern California Earthquake Center Annual Meeting, Palm Springs, CA, Sept 2015.
Conference Tutorials
Machine Learning for Seismology Workshop, Seismological Society of America Annual Meeting, Seattle, WA, April 2019. [ workshop website ] [ slides ]
Unsupervised Learning for Geoscience Applications, Machine Learning in Solid Earth Geoscience Conference, Santa Fe, NM, March 2019. [ conference website ] [ slides ]
Introduction to Machine Learning Workshop, SIAM Geosciences Conference, Stanford University, June 2015. [ conference website ] [ workshop website ]
Panels
Harvard FAS Office of Postdoctoral Affairs, Tales from the Battlefront: Q&A Among Survivors and Casualties of the Academic Job Search, June 2020.
Women in Data Science @ Stanford Earth Workshop, Stanford University, CA, Nov 2019.
National Academies Committee on Seismology and Geodynamics Fall Meeting, Washington, D.C., Oct 2019.
Machine Learning in Solid Earth Geoscience Conference, Santa Fe, NM, Mar 2019.
Society of Exploration Geophysics Annual Meeting, Workshop on Data Analytics for Geoscience, Houston, TX, Sept 2017.