My research focuses on developing and applying new techniques to analyze large datasets of seismic waveforms in order to better understand earthquake rupture processes and their relation to seismic hazards. I am broadly interested in leveraging concepts from big data and scientific machine learning alongside high-fidelity physical modeling in order to advance earthquake science.
My research team at UNR works on a wide range of projects across earthquake science. Topics of particular interest include:
- Earthquake source properties (magnitude, stress drop, and radiated energy estimates)
- Earthquake nucleation and rupture dynamics
- Stress transfer and earthquake triggering
- Earthquake early warning
- Ground motion prediction
- Forensic seismology and nuclear monitoring
- Earthquake geodesy, strain accumulation, in relation to hazard
Ph.D., Earth Sciences, University of California-San Diego, 2017
MS, Earth Sciences, University of California-San Diego, 2015
BS, Geophysics, Stanford University, 2013
- Shearer, PM, RA Abercrombie, and DT Trugman (2022). Improved stress drop estimates for M 1.5 to 4 earthquakes in Southern California from 1996 to 2019. Journal of Geophysical Research: Solid Earth, e2022JB024243, doi: 10.1029/2022JB024243.
- Bolton, DC, S. Sharan, G. McLaskey, J. Riviere, P. Shokouhi, DT Trugman, and C. Marone (2022). The high-frequency signature of slow and fast laboratory earthquakes. Journal of Geophysical Research: Solid Earth, e2022JB024170, doi: 10.1029/2022JB024170.
- Arrowsmith, SJ, DT Trugman, J. MacCarthy, KJ Bergen, D. Lumley, and BM Magnani (2022). Big data seismology. Reviews of Geophysics, 60, e2021RG000769, doi: 10.1029/2021RG000769.
- Trugman, D. T. (2022). Resolving differences in the rupture properties of M5 earthquakes in California using Bayesian source spectral analysis. Journal of Geophysical Research: Solid Earth, 127 (4), e2021JB023526, doi: 10.1029/2021JB023526.
- Corradini, M., IW McBrearty, DT Trugman, C. Satriano, PA Johnson, and P. Bernard (2022). Investigating the influence of earthquake source complexity on back-projection images using convolutional neural networks. Geophysical Journal International, ggac026, doi: 10.1093/gji/ggac026.
- Saad, OM, Y. Chen, DT Trugman, MS Soliman, L. Samy, A. Savvaidis, MA Khamis, AG Hafez, S. Fomel, and Y. Chen (2022). Machine learning for fast and reliable source-location estimation in earthquake early warning. IEEE Transactions on Geoscience and Remote Sensing, 19, pp.1-5, doi: 10.1109/LGRS.2022.3142714.
- Wang, W., PM Shearer, J. Vidale, X. Xu, DT Trugman, and Y. Fialko (2022). Tidal modulation of seismicity at the Coso geothermal field. Earth and Planetary Science Letters, 579, 117335, doi: 10.1016/j.epsl.2021.117335.
- Chu, SX, VC Tsai, DT Trugman, and G. Hirth (2021). Fault interactions enhance high-frequency earthquake radiation. Geophysical Research Letters, 48, e2021GL095271, doi: 10.1029/2021GL095271.
- Abercrombie, RE, DT Trugman, PM Shearer, X. Chen, J. Zhang, CN Pennington, JL Hardebeck, THW Goebel, and CJ Ruhl (2021). Does earthquake stress drop increase with depth in the crust? Journal of Geophysical Research: Solid Earth, 126, e2021JB022314, doi: 10.1029/2021JB022314.
- Trugman, DT, SX Chu, and VC Tsai (2021). Earthquake source complexity controls the frequency-dependence of near-source radiation patterns. Geophysical Research Letters, 48, e2021GL095022, doi: 10.1029/2021GL095022.
- Tsai, VC, G. Hirth, DT Trugman, and SX Chu (2021). Impact versus frictional earthquake models for high-frequency radiation in complex fault zones. Journal of Geophysical Research: Solid Earth 126, e2021JB022313, doi: 10.1029/2021JB022313.
- Skoumal, RJ, and DT Trugman (2021). The proliferation of induced seismicity in the Permian Basin. Journal of Geophysical Research: Solid Earth, 126, e2021JB021921, doi: 10.1029/2021JB021921.
- Trugman, DT, and A. Savvaidis (2021). Source spectral properties of earthquakes in the Delaware Basin of West Texas. Seismological Research Letters, 92 (4): 2477–2489, doi: 10.1785/0220200461.
- Wang, T., D. T. Trugman, and Y. Lin (2021). SeismoGen: Seismic waveform synthesis using generative adversarial networks. Journal of Geophysical Research: Solid Earth, 126, e2020JB020077, doi: 10.1029/2020JB020077.
- Trugman, DT, IW McBrearty, DC Bolton, RA Guyer, C. Marone, and PA Johnson (2020). The spatiotemporal evolution of granular microslip precursors to laboratory earthquakes. Geophysical Research Letters, 47 (16), e2020GL088404, doi: 10.1029/2020GL088404.
- Ross, ZE, ES Cochran, DT Trugman, and JD Smith (2020). 3D fault architecture controls the dynamism of earthquake swarms. Science, 368 (6497), 1357–1361, doi: 10.1126/science.abb0779.
- Trugman, D. T. (2020). Stress drop and source scaling of the 2019 Ridgecrest, California, earthquake sequence. Bulletin of the Seismological Society of America, 110 (4), 1859-1871, doi: 10.1785/012020009.
- Trugman, DT, Z.E. Ross, and PA Johnson (2020). Imaging stress and faulting complexity through earthquake waveform similarity. Geophysical Research Letters, 47 (1), e2019GL085888, doi: 10.1029/2019GL085888.
- Ross, ZE, DT Trugman, K. Azizzadenesheli, and A. Anandkumar (2020). Directivity modes of earthquake populations with unsupervised learning. Journal of Geophysical Research: Solid Earth, 125 (2), e2019JB018299, doi: 10.1029/2019JB018299.
- Qin, Y., X. Chen, JI Walter, J. Haffener, DT Trugman, BM Carpenter, M. Weingarten, and F. Kolawole (2019). Deciphering the stress state of seismogenic faults in Oklahoma and Southern Kansas based on an improved stress map. Journal of Geophysical Research: Solid Earth, 124, 12920–12934, doi: 10.1029/2019JB018377.
- Trugman, D. T., and Z. E. Ross (2019). Pervasive foreshock activity across Southern California. Geophysical Research Letters, 46 (15), 8772-8781, doi: 10.1029/2019GL083725.
- Ross, ZE, DT Trugman, Hauksson, E., and Shearer, PM (2019). Searching for hidden earthquakes in Southern California. Science, 364(6442), 767–771, doi: 10.1126/science.aaw6888.
- Trugman, DT, MT Page, SE Minson, and ES Cochran (2019). Peak ground displacement saturates exactly when expected: Implications for earthquake early warning. Journal of Geophysical Research: Solid Earth, 124 (5), 4642–4653, doi: 10.1029/2018JB017093.
- Shearer, PM, RA Abercrombie, DT Trugman, and W. Wang (2019). Comparing EGF methods for estimating corner frequency and stress drop from P-wave spectra. Journal of Geophysical Research: Solid Earth, 124 (4), 3966-3986, doi: 10.1029/2018JB016957.
- Kong, Q., DT Trugman, ZE Ross, MJ Bianco, BJ Meade, and P. Gerstoft (2019). Machine learning in seismology – Turning data into insights. Seismological Research Letters, 90(1), 3-14, doi: 10.1785/0220180259.
- Koper, KD, KL Pankow, JC Pechmann, JM Hale, R. Burlacau, WL Yeck, HM Benz, RB Hermann, DT Trugman, and PM Shearer (2018). Afterslip enhanced aftershock activity during the 2017 earthquake sequence near Sulfur Peak, Idaho. Geophysical Research Letters, 45, 5352–5361, doi: 10.1029/2018GL078196.
- Trugman, DT, and PM Shearer (2018). Strong correlation between stress drop and peak ground acceleration for recent M1-M4 seismicity in the San Francisco Bay Area. Bulletin of the Seismological Society of America, 108 (2), 929-945, doi: 10.1785/0120170245.
- Trugman, DT, SL Dougherty, ES Cochran, and PM Shearer (2017). Source spectral properties of small to moderate earthquakes in Southern Kansas. Journal of Geophysical Research: Solid Earth, 122 (10), 8021–8034, doi: 10.1002/2017JB014649.
- Trugman, DT, and PM Shearer (2017). Application of an improved spectral decomposition method to examine earthquake source scaling in Southern California. Journal of Geophysical Research: Solid Earth, 122 (4), 2890–2910, doi: 10.1002/2017JB013971.
- Trugman, DT, and PM Shearer (2017). GrowClust: A hierarchical clustering algorithm for relative earthquake relocation, with application to the Spanish Springs and Sheldon, Nevada, earthquake sequences. Seismological Research Letters, 88 (2A), 379–391, doi: 10.1785/0220160188.