Geophysics · Machine Learning · Signal Processing
Ph.D. — Seismologist & AI/ML Researcher
Applying deep learning and probabilistic methods to problems in seismology, geosciences, and signal intelligence.
01 — About
I work at the intersection of geophysics and machine learning, developing
tools and models that bridge traditional scientific methods with modern AI.
My background spans earthquake seismology, ambient noise tomography, RF
signal intelligence, and rare earth element characterization.
I hold a Ph.D. in Geophysics from the University of Utah (4.0 GPA) and
completed a Mendenhall Postdoctoral Fellowship at the USGS National
Earthquake Information Center before joining Idaho National Laboratory.
02 — Projects
AI Framework
Flexible framework for accessible, automatic application of AI and ML to scientific data. Features auto-encoders and dimensionality reduction wrappers for rapid deployment across diverse input types.
RF Signal Intelligence
ML pipeline for portable detection, classification, and open-set recognition of unknown wireless signals. Uses GANs, CNNs, and transformer architectures deployed on field hardware.
Seismology · Deep Learning
ML-based pipeline for reliable global seismic P and S phase identification, built for integration into daily USGS NEIC operations. Extended existing architectures with improved training methods.
Geoscience · ML
Supervised ML for categorical monazite classification; addressing fundamental data scarcity challenges in rare earth element geoscience with global dataset curation.
Energy · Physics-Informed ML
Physics-informed neural networks to explore parameter space (temperature, grain size) for optimal subsurface serpentinization conditions, accelerating clean hydrogen production research.
Cyber Security · Anomaly Detection
Unsupervised and deep learning methods to identify anomalous network communication activity within INL infrastructure, targeting production deployment.
03 — Publications
IEEE Transactions on Signal Processing
A Comparative Analysis of Feature Extraction and Distance Loss Functions for Unknown Waveform Detection in the Time-Frequency Domain
In PreparationIEEE ICC 2025
Contrasting Time-Frequency Representations for Unknown Waveform Detection
Seismica
Evidence for interaction of Wasatch Fault segments at depth
In PreparationBulletin of the Seismological Society of America
Wasatch Fault Structure from Machine Learning Arrival Times and High-Precision Earthquake Locations
↗ DOI: 10.1785/0120230247Journal of Geophysical Research: Solid Earth
Combining dense seismic arrays and broadband data to image the subsurface velocity structure in geothermally active South-central Utah
↗ DOI: 10.1029/2022JB024070Seismological Research Letters
Responding to the 2020 Magna, Utah earthquake sequence during the COVID-19 pandemic shutdown
↗ DOI: 10.1785/022020026504 — CV
Research Data Scientist
Idaho National Laboratory
2024 – Present
Mendenhall Postdoctoral Research Geophysicist
U.S. Geological Survey, Golden CO
2023 – 2024
Graduate Research Assistant & Duty Seismologist
University of Utah
2018 – 2023
Graduate Geophysics Intern
Sandia National Laboratories
2020 – 2023
PI — NNSA (NA-241) · $130,000
Seismic Sensor Infrastructure at WIPP
2025
Co-I — INL LDRD · $688,000
GREENR — Rare Earth Element Geometallurgy
2024
Mendenhall Fellowship · ~$300,000
Machine Learning for Global Seismology
2023
Ph.D. — Geophysics
University of Utah · 4.0 GPA
2018 – 2023
B.S. — Geophysics
Western Washington University · 3.81 GPA
2012 – 2016
US202250192904A1
Spectrum Monitoring and Analysis (WiFIRE)
US11251889B2
Wireless Signal Monitoring and Analysis (WiFIRE)
US12418349B2
Spectrum Monitoring and Analysis (WiFIRE)
05 — Contact
Open to research collaborations, consulting, and discussions at the intersection of geophysics and machine learning. Feel free to reach out.
📍 Pocatello, ID 83201