Presentations

Interviews

Big data for small earthquakes: data mining, deep learning, and explainable AI

USGS Earthquake Science Seminar (2022^^); University of Montana, Missoula, MT (2022^^); University of Oslo, Norway (2022^^); Cornell University, Ithaca, NY (2021^^); University of Utah, Salt Lake City, UT (2021^^); MIT, Cambridge, MA (2021).

Earthquake monitoring, Deep learning and Explainable AI

NSF AI Institute for Data-Driven Discovery in Physics Seminar, Carnegie Mellon University (2022^^)

Explainable AI for Seismology: An interpretable convolutional neural network for earthquake detection

GNEM Seminar, Sandia National Laboratory (2023^^); Symposium on Artificial Intelligence and Earthquake Engineering, EERI San Diego Chapter (2022^^); Brazilian Seismology Symposium, International Congress of the Brazilian Geophysical Society (2021^^).

Big Data Analysis in Geoscience

International Symposium: Frontier of Understanding Earth’s Interior and Dynamics, Tohoku University, Sendai, Japan (2022^^).

Machine Learning in Seismology: A Fireside Chat

Plenary panel with Qingkai Kong and Daniel Trugman, moderated by Bill Walter. Seismological Society of America Annual Meeting (2021^^). [recording]

Advancing solid Earth geoscience with machine learning

Geological Society of Washington, Washington, D.C. (2021^^) [ announcement ]. Winner: 2021 Sleeping Bear Award for good humor at meetings.

Distributed acoustic sensing (DAS) and big scientific data analysis

Distributed Acoustic Sensing Virtual Workshop and Tutorial, IRIS (2020^^). [ workshop website ] [ video ( + captions) ] [ slides ]

Event detection in big sensor data: Applications in earthquake seismology and beyond

Life on Planet Earth: Above and Below Workshop, Mathematical Biosciences Institute, Ohio State University, Columbus, OH (2020^^). [ workshop website ] [ video ]

Big data for small earthquakes: Computational challenges in large-scale earthquake detection

University of Delaware, Newark, DE (2020^^); Boston University, Boston, MA (2020^^); University of California, Santa Barbara, CA (2020); University of British Columbia, Vancouver, Canada (2020); Brown University, Providence, RI (2020); Colorado School of Mines, Golden, CO (2020); University of Texas at Austin, TX (2020); Michigan State University, East Lansing, MI (2020).

Machine learning for data-driven discovery in solid Earth geoscience.

National Academies Committee on Seismology and Geodynamics Fall Meeting. Washington, DC (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, (2019) [ news release ]; Princeton University, Princeton, NJ (2019); University of Texas at Austin, TX (2019) [ video ] [ slides ].

Data mining for earthquake detection: Lessons for data-driven geoscience.

Machine Learning in Solid Earth Geoscience Conference, Santa Fe, NM (2019). [ conference website ]

Machine Learning in Seismology: Using AI to Improve Earthquake Monitoring.

Congressional briefing (with Zach Ross), hosted by the Seismological Society of America, Washington D.C. (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 (2018). [ workshop website ]

Improving earthquake detection with data mining and machine learning.

IRIS Workshop: Foundations, Frontiers & Future Facilities for Seismology, Albuquerque, NM (2018). [ workshop website ] [ abstract ] [ slides ]

Big data for small earthquakes: a data mining approach to large-scale earthquake detection.

University of Washington, Seattle, WA (2019); Columbia University, Palisades, NY (2019); Brown University, Providence, RI (2018); Sandia National Laboratory, Livermore, CA, (2018); MIT, Cambridge, MA (2018). [ recording ]

FAST: Earthquake Detection using Computationally Efficient Similarity Search.

Earthquake Science Seminar (with Clara Yoon), US Geological Survey, Menlo Park, CA (2015). [ recording ]

^^ indicates virtual talk

Machine Learning for Seismology Workshop, Seismological Society of America Annual Meeting, Seattle, WA (2019). [ workshop website ] [ slides ]
Unsupervised Learning for Geoscience Applications, Machine Learning in Solid Earth Geoscience Conference, Santa Fe, NM (2019). [ conference website ] [ slides ]
Introduction to Machine Learning Workshop, SIAM Geosciences Conference, Stanford University (2015). [ conference website ] [ workshop website ]

Harvard FAS Office of Postdoctoral Affairs, Tales from the Battlefront: Q&A Among Survivors and Casualties of the Academic Job Search (2020^^).