معرفی
Dr. Daniel Trugman is an Assistant Professor in the Department of Geological Sciences and Engineering at the University of Nevada, Reno (UNR), affiliated with the Mackay School of Earth Sciences and Engineering. He holds a BS in Geophysics from Stanford University and MS/PhD in Earth Sciences from Scripps Institution of Oceanography at UC San Diego. Previously, he was a Richard P. Feynman Postdoctoral Fellow at Los Alamos National Laboratory (2018–2020) and an Assistant Professor at the University of Texas at Austin (2020–2022). His research focuses on earthquake rupture processes, seismic hazards, and leveraging machine learning and big data in seismology. He leads projects at the Nevada Seismological Laboratory, investigating Nevada seismicity, fault interactions, and earthquake early warning systems.
Education:
• Ph.D., Earth Sciences, UC San Diego (2017)
• M.S., Earth Sciences, UC San Diego (2015)
• B.S., Geophysics, Stanford University (2013)
Research interests include:
- Nevada seismicity and tectonics
- Earthquake source properties (stress drop, radiated energy)
- Seismic hazard analysis
- Machine learning for glacier dynamics and seismic monitoring
- Induced seismicity and fracking impacts
Awards:
- Charles F. Richter Early Career Award (2023)
- Mousel-Feltner Award for Research Excellence (2023)
His work integrates high-fidelity physical modeling with data-driven techniques, including studies on glacier basal sliding, ground motion prediction, and fault network complexity. He teaches courses on Python for Earth Sciences and earthquake engineering.
Labs/Teams: Active member of the Nevada Seismological Laboratory and collaborates with the Southern California Earthquake Center (SCEC) and USGS.
