About Me

For many years, I played and taught music in the Bay Area, California. At some point, I discovered physics and decided to turn to studying our natural world. My research focuses on source processes from seismic phenomena including glacial icequakes and repeating earthquake sequences on the San Andreas Fault, namely by implementing unsupervised machine-learning methods to large seismic datasets. I also apply machine-learning techniques to help understand near-field source processes of moderate-to-large earthquakes using distributed acoustic sensing (DAS), that is, fiber optic cables. My work has a diverse range of applications, from earthquake early warning to understanding glacial behavior as a response to warming temperatures.

Dr. Theresa Sawi (and Prince)

Research

My research interests include:

• Source processes of glacial and terrestrial earthquakes
• Earthquake early warning
• Machine learning and cloud computing for seismology
• Unsupervised Feature Extraction for Spectrograms: SpecUFEx

Publications

Here are some of my recent publications:

• Sawi, T., Waldhauser, F., Holtzman, B., Groebner N. (2023) Detecting repeating earthquakes on the San Andreas Fault with unsupervised machine-learning of spectrograms. The Seismic Record; 3 (4): 376–384. Link
• Sawi, T., Holtzman, B., Walter, F., & Paisley, J. (2022) An unsupervised machine-learning approach to understanding seismicity at an alpine glacier. Journal of Geophysical Research: Earth Surface, 127, e2022JF006909. Link
• Carr B., Lev E., Sawi, T., Bennett K., Edwards C., Soule A., Vargas S., Marliyani G., Clarke A., (2021) Mapping and classification of volcanic deposits using multi-sensor Unoccupied Aerial Systems. Remote Sensing of Environment 264, 112581. Link
• Sawi, T., and M. Manga (2018) Revisiting short-term earthquake triggered volcanism. Bulletin of Volcanology. 80. Link

See full publication list here: Google Scholar

Conference Presentations

• Sawi, T., Waldhauser, F., Holtzman, B., Groebner, N. (2023). Detecting Repeating Earthquakes on the San Andreas Fault with Unsupervised Machine-Learning of Spectrograms. Workshop on Earthquake Physics and Applications of Machine Learning to Tectonic Faulting, 18-22 Sep. Rome, Italy.
• Sawi, T., Waldhauser, F., Holtzman, B., Groebner, N. (2023). A Semi-Supervised Machine-Learning Approach to Detecting Repeating Earthquakes on the San Andreas Fault. SSA Annual Meeting, Puerto Rico.
• Sawi, T., Waldhauser, F., Holtzman, B., Beauce, E., Wang, K., Groebner, N. (2022). A Semi-Supervised Machine-Learning Approach to Detecting Repeating Earthquakes on the San Andreas Fault. AGU Fall Meeting, Chicago.
• Wang, K., Waldhauser, F., Sawi, T., Beauce, E., Schaff, D.P., Groebner, N., Tolstoy, M., Wilcock, W.S., Tan, Y.J. (2022). Mining a large earthquake catalog at Axial Seamount with unsupervised spectral feature extraction method. AGU Fall Meeting, Chicago.
• Saltiel, S., McCarthy, C., Holtzman, B., Sawi, T., Savage, H. (2021). Characterization of seismicity over a range of subglacial slip conditions: laboratory investigation of ice stick-slip acoustic emissions. In AGU Fall Meeting Abstracts (pp. S55B-0132).
• Birnbaum, J., Carchedi, C., Lee, M., Sawi, T., Russell, J. (2021). Browser-based Visualization of Seismic Records to Build Seismogram Literacy. In AGU Fall Meeting Abstracts (pp. ED15A-0521).
• Holtzman, B., Groebner, N., Sawi, T., Xing, T., Pec, M., Ghaffari, H., Mok, U., Skarbek, R., Paisley, J., Mittal, T., Waldhauser, F., Beauce, E., Barth, A. (2021). Unsupervised spectral feature extraction applied to acoustic emissions during brittle creep of basalt under dry and wet conditions. In AGU Fall Meeting Abstracts (pp. H12E-04).
• Sawi, T., DeShon, H., Ogwari, P., Quinones, L. (2017). Imaging fault structure using cross-correlation and relative earthquake location from the IRIS Wavefields community dataset in Oklahoma. In AGU Fall Meeting Abstracts (pp. S23C-0833).