Jared Smith
Machine Learning Specialist at U.S. Geological Survey (USGS)
Reston, Virginia, United States
Summary
👤
Senior🎓
Top SchoolJared Smith is a Machine Learning Specialist at the U.S. Geological Survey with a decade of experience applying statistical and spatial-data methods to environmental and water-resources challenges. Trained with a PhD from Cornell, he blends Bayesian inference, global sensitivity analysis, and stochastic optimization with process-guided deep learning to produce robust, decision-relevant models for flood prediction, watershed management, and geothermal resource assessment. His work spans practical applications—optimizing green infrastructure placement under uncertainty in the Chesapeake Bay watershed—to probabilistic geothermal playfairway analyses for direct-use heating across the Appalachian Basin. Comfortable bridging academic research and government practice, he often couples physical process models with modern ML to improve interpretability and resilience of predictions. An uncommon strength is his track record of turning geostatistical uncertainty quantification into actionable site-selection and techno-economic insights for energy and water systems.
10 years of coding experience
9 years of employment as a software developer
Research Exchange Student, Research Exchange Student at Iceland School of Energy - at Reykjavik UniversityExchange Student, Exchange Student at University of NewcastleBachelor's Degree, Bachelor's Degree at Clarkson UniversityDoctor of Philosophy (Ph.D.), Doctor of Philosophy (Ph.D.) at Cornell UniversityHigh School, High School at Islip High School
Stackoverflow
280reputation
33kreached
11answers
2questions
Github Skills (98)
jam10
predict10
drb10
frequency-analysis10
logistic-regression10
regression9
prediction9
bootstrap9
region9
systems-biology8
water8
environmental8
ice8
delta8
traits8
Programming languages (5)
Github contributions (5)
USGS-R/drb-inland-salinity-ml
Oct 2021 - Nov 2022
Code repo for Delaware River Basin machine learning models that predict inland salinity.
Contributions:280 reviews, 363 commits, 87 PRs in 1 year 1 month
riverpredictmachine-learningbasindelaware
jds485/PAD_IceJamFloods
May 2018 - Dec 2022
Frequency analysis for ice jam floods applied in the Peace-Athabasca Delta, Canada. Serves as the paper code repository for Timoney et al. (2018) and Lamontagne et al. (in prep).
Contributions:7 releases, 116 commits, 1 PR in 4 years 7 months
peace-athabasca-deltapaper-codefrequency-analysisservesice
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