Warren Davis

Sandia National Laboratories — United States

Physics and Astronomy · Physical Sciences

7h-index155citations40works0.82yr avg
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Research Topics

Model Reduction and Neural Networks(4), Anomaly Detection Techniques and Applications(3), Data Stream Mining Techniques(3), Climate variability and models(2), Fluid Dynamics and Turbulent Flows(2)

Publications40 total

A Parametric, Data-Driven, Non-Intrusive Reduced-Order Model Framework for Crystal Plasticity Simulations of Voids
Integrating materials and manufacturing innovation·2025
Spatio-temporal multivariate cluster evolution analysis for detecting and tracking climate impacts
Journal of Computational and Applied Mathematics·2025· 2 citedOpen Access
A hybrid machine learning model for predicting gene expression from epigenetics across fungal species
2024· 2 citedOpen Access
Spatio-temporal Multivariate Cluster Evolution Analysis for Detecting and Tracking Climate Impacts
arXiv (Cornell University)·2024Open Access
BeyondFingerprinting: AI-guided discovery of robust materials & processes
2024Open Access
CLimate Impact: Determining Etiology thRough pAthways (CLDERA)
2024· 1 citedOpen Access
Anomaly Detection in Materials Digital Twins with Multiscale ICME for Additive Manufacturing
Integrating materials and manufacturing innovation·2024· 1 cited
MAPLE v.1.0
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)·2024Open Access
Application of In-Situ Machine Learning Towards Climate Simulation Analysis and Discovery
2023Open Access
A Novel In Situ Machine Learning Framework for Intelligent Data Capture and Event Detection
Lecture notes in energy·2023· 2 citedOpen Access
In-Situ Machine Learning (ISML)
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)·2022Open Access
Predicting Mechanical Performance in Additive Manufacturing Components Using Deep Learning.
2021Open Access
In-Situ Machine Learning for Intelligent Data Capture on Exascale Platforms.
2021Open Access
Climate Intervention Assessment and Attribution
2021· 1 citedOpen Access
Advancing Sea Ice Predictability in E3SM with Machine Learning
2021Open Access
Water Cycle-Driven Infectious Diseases as Multiscale, Reliable, Continuously Updating Water Cycle Sensors
2021Open Access
Using Deep Neural Networks to Predict Material Types in Conditional Point Sampling Applied to Markovian Mixture Models
2021· 1 cited
Arctic Tipping Points Triggering Global Change (LDRD Final Report)
2020· 5 citedOpen Access
Predicting Future Disease Burden in a Rapidly Changing Climate
2020· 1 citedOpen Access
The Potential of Integrated Machine Learning Algorithms for Tropical Cyclone Detection in Advanced Climate Modeling
OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)·2019Open Access
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Frequent Co-authors

Irina Tezaur(9), Kara Peterson(8), Timothy M. Shead(7), Hemanth Kolla(6), Daniel Dunlavy(5), Julia Ling(4), Max Carlson(4), Laura Swiler(4), Konduri Aditya(3), W. Philip Kegelmeyer(3), Matthew Barone(3), Kenny Chowdhary(3), Jeffrey A. Fike(3), Erika Roesler(3), Diana Bull(3), Max Carlson(3), Kevin A. Reed(2), Ladislav Kohout(2), Amy Powell(2), Matthew Gregor Peterson(2)