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Publication	Type	Year
The Trusted Artificial Intelligence Research Campaign Artificial Intelligence for Robust Engineering & Science David John Stracuzzi	Conference Presentation – 2022 Conference Presentation	2022
Overview of ML/AI at Sandia BNL workshop on AI/ML for Safeguards Michael Reed Smith, Nancy Kay Hayden, David John Stracuzzi, Nathan Shoman	Presentation (non-conference) – 2022 Presentation (non-conference)	2022
WORKSHOP REPORT: AI-Enhanced Co-Design for Next-Generation Microelectronics: Innovating Innovation Michael R. Descour, Jeffrey Y. Tsao, David John Stracuzzi, Anna K Wakeland, David R. Schultz, William Smith, Jacquilyn Anne Weeks https://www.osti.gov/search/identifier:1845383	Report – 2021 Report	2021
Exploring Explicit Uncertainty for Binary Analysis (EUBA) Michelle A. Leger, Michael Christopher Darling, Stephen T. Jones, Laura E. Matzen, David John Stracuzzi, Andrew T. Wilson, Denis Bueno, Matthew Christentsen, Melissa Ginaldi, David Alexander Hannasch, Scott Heidbrink, Breannan Carole Howell, Chris L. Leger, Geoffrey Edward Reedy, Alisa Nicole Rogers, Jack Arthur Williams https://www.osti.gov/search/identifier:1832314	SAND Report – 2021 SAND Report	2021
Using Uncertainty and Out-of-distribution Detection to Identify Unreliable Predictions Artificial Intelligence and Statistics 2022 Michael Christopher Darling, Justin E Doak, Richard V. Field, Mark A. Smith, David John Stracuzzi	Abstract – 2021 Abstract	2021
Optimizing Machine Learning Predictions with Prediction Uncertainty Sandia Academic Alliance/ UT Austin Student LDRD Poster Session Zachary J. Smith, Michael Christopher Darling, David John Stracuzzi, Justin E Doak, Mark A. Smith, J. Eric Bickel https://www.osti.gov/search/identifier:1860307	Conference Poster – 2021 Conference Poster	2021
AI Training for DOE Leadership DOE AI Leadership Training Courtney Corley, David John Stracuzzi https://www.osti.gov/search/identifier:1860304	Presentation (non-conference) – 2021 Presentation (non-conference)	2021
Generating Uncertainty Distributions for Seismic Signal Onset Times Bulletin of the Seismological Society of America Matthew Gregor Peterson, David John Stracuzzi, Christopher J. Young, Charles Vollmer, Ronald Brogan https://www.osti.gov/search/identifier:1781564	Journal Article – 2021 Journal Article	2021
Robustness and Validation of Model and Digital Twins Deployment Svitana Volkova, David John Stracuzzi, Jenifer Shafer, Jaideep Ray, Laura Pullum https://www.osti.gov/search/identifier:1770631	Report – 2021 Report	2021
Preliminary Work on a Digital Twin for Cancer Patients ARTIFICIAL INTELLIGENCE FOR ROBUST ENGINEERING & SCIENCE David John Stracuzzi https://www.osti.gov/search/identifier:1854684	Conference Presentation – 2021 Conference Presentation	2021
Preliminary Work on a Digital Twin for Cancer Patients Artificial Intelligence for Robust Engineering and Science David John Stracuzzi	Abstract – 2020 Abstract	2020
Research Needs for Trusted Analytics in National Security Settings NIST AI Assurance Mini-Workshop David John Stracuzzi, Ann Speed https://www.osti.gov/search/identifier:1832675	Presentation (non-conference) – 2020 Presentation (non-conference)	2020
Models of Models: Recognizing and Managing the Uncertainties of Machine Learning in Engineering Applications Uncertainty Management and Machine Learning in Engineering Applications David John Stracuzzi https://www.osti.gov/search/identifier:1831563	Conference Presentation – 2020 Conference Presentation	2020
Models of Models: Recognizing and Managing the Uncertainties of Machine Learning in Engineering Applications Uncertainty Management and Machine Learning in Engineering Applications David John Stracuzzi	Abstract – 2020 Abstract	2020
Pattern of Life Behavior Recognition in Seismic Data Aistats David John Stracuzzi, Erick Clint Draayer	Abstract – 2020 Abstract	2020
Measuring and Extracting Activity from Time Series Data David John Stracuzzi, Matthew Gregor Peterson, Gabriel ANUOLUWAPO Popoola https://www.osti.gov/search/identifier:1673451	SAND Report – 2020 SAND Report	2020
Arctic Tipping Points Triggering Global Change LDRD Final Report Kara J. Peterson, Amy Jo Powell, Irina Kalashnikova Tezaur, Erika Louise Roesler, Jeffrey Nichol, Matthew Gregor Peterson, Warren Leon Davis, John Davis Jakeman, David John Stracuzzi, Diana L Bull https://www.osti.gov/search/identifier:1669210	SAND Report – 2020 SAND Report	2020
Research Needs for Trusted Analytics in National Security Settings David John Stracuzzi, Ann Speed https://www.osti.gov/search/identifier:1662023	Report – 2020 Report	2020
Machine Learning to Compare Arctic Simulations With Observed Data European Seminar on Computing 2020 Jeffrey Nichol, Matthew Gregor Peterson, Kara J. Peterson, David John Stracuzzi, Matthew Fricke https://www.osti.gov/search/identifier:1807391	Conference Paper – 2020 Conference Paper	2020
A Novel Measure of Uncertainty For Machine Learning Predictions Conference On Data Analytics (CoDA) Michael Christopher Darling, Don R. Hush, David John Stracuzzi https://www.osti.gov/search/identifier:1768156	Conference Paper – 2020 Conference Paper	2020
Project Management from the Perspective of a Principal Investigator Program Magament Institute RGC Monthly Meeting David John Stracuzzi	Presentation (non-conference) – 2020 Presentation (non-conference)	2020
Event Detection and Characterization in a Network of Subsurface Sensors CoDA 202, Conference on Data Analysis Charles Vollmer, David John Stracuzzi, Paul Conrad Schwering, Christian Poppeliers, Didem G. Beskardes	Abstract – 2020 Abstract	2020
Comparing Simulated and Observed Data with Random Forest Feature Importance Conference on Data Analysis Jeffrey Nichol, Matthew Gregor Peterson, Kara J. Peterson, David John Stracuzzi https://www.osti.gov/search/identifier:1766757	Conference Paper – 2020 Conference Paper	2020
Using Anomaly Detection for Activity Identification CoDA 2020 Gabriel ANUOLUWAPO Popoola, Matthew Gregor Peterson, David John Stracuzzi	Conference Paper – 2020 Conference Paper	2020
Machine Learning to Compare Arctic Simulations with Observed Data European Seminar on Computing 2020 Jeffrey Nichol, Matthew Gregor Peterson, Warren Leon Davis, Kara J. Peterson, David John Stracuzzi	Abstract – 2020 Abstract	2020
Document Title	Type	Year

Results 1–25 of 107

Publications

The Trusted Artificial Intelligence Research Campaign

Overview of ML/AI at Sandia

WORKSHOP REPORT: AI-Enhanced Co-Design for Next-Generation Microelectronics: Innovating Innovation

Exploring Explicit Uncertainty for Binary Analysis (EUBA)

Using Uncertainty and Out-of-distribution Detection to Identify Unreliable Predictions

Optimizing Machine Learning Predictions with Prediction Uncertainty

AI Training for DOE Leadership

Generating Uncertainty Distributions for Seismic Signal Onset Times

Robustness and Validation of Model and Digital Twins Deployment

Preliminary Work on a Digital Twin for Cancer Patients

Preliminary Work on a Digital Twin for Cancer Patients

Research Needs for Trusted Analytics in National Security Settings

Models of Models: Recognizing and Managing the Uncertainties of Machine Learning in Engineering Applications

Models of Models: Recognizing and Managing the Uncertainties of Machine Learning in Engineering Applications

Pattern of Life Behavior Recognition in Seismic Data

Measuring and Extracting Activity from Time Series Data

Arctic Tipping Points Triggering Global Change LDRD Final Report

Research Needs for Trusted Analytics in National Security Settings

Machine Learning to Compare Arctic Simulations With Observed Data

A Novel Measure of Uncertainty For Machine Learning Predictions

Project Management from the Perspective of a Principal Investigator

Event Detection and Characterization in a Network of Subsurface Sensors

Comparing Simulated and Observed Data with Random Forest Feature Importance

Using Anomaly Detection for Activity Identification

Machine Learning to Compare Arctic Simulations with Observed Data