Publications

Tsao, J.Y., Abbott, R.G., Crowder, D.C., Desai, S., Dingreville, R.P.M., Fowler, J.E., Garland, A., Murdock, J.M., Steinmetz, S.T., Yarritu, K.A., Johnson, C.M., Stracuzzi, D.J., Padmanabha Iyer, P., & Padmanabha Iyer, P. (2024). AI for Technoscientific Discovery: A Human-Inspired Architecture. Journal of Creativity (Online), 34(2). https://doi.org/10.1016/j.yjoc.2024.100077

Stracuzzi, D.J., Carvey, B.J., & Carvey, B.J. (2023). Paraview Omniverse Scientific Visualization [Conference Presenation]. https://doi.org/10.2172/2431418

Darling, M.C., Field, R.V., Smith, M.A., Doak, J.E., Headen, J.M., Stracuzzi, D.J., & Stracuzzi, D.J. (2022). Decision Science for Machine Learning (DeSciML). https://doi.org/10.2172/1903086

Stracuzzi, D.J. (2022). The Trusted Artificial Intelligence Research Campaign [Conference Presenation]. https://doi.org/10.2172/2002431

Leger, M., Darling, M.C., Jones, S.T., Matzen, L.E., Stracuzzi, D.J., Wilson, A.T., Bueno, D., Christentsen, M., Ginaldi, M., Bachman, W.B., Heidbrink, S., Howell, B.C., Leger, C., Reedy, G., Rogers, A.N., Williams, J., & Williams, J. (2021). Exploring Explicit Uncertainty for Binary Analysis (EUBA). https://doi.org/10.2172/1832314

Descour, M., Tsao, J.Y., Stracuzzi, D.J., Wakeland, A., Schultz, D., Smith, W., Weeks, J., & Weeks, J. (2021). AI-Enhanced Co-Design for Next-Generation Microelectronics: Innovating Innovation (Workshop Report). https://doi.org/10.2172/1845383

Corley, C., Stracuzzi, D.J., & Stracuzzi, D.J. (2021). AI Training for DOE Leadership [Presentation]. https://www.osti.gov/biblio/1860304

Smith, Z.J., Darling, M.C., Stracuzzi, D.J., Doak, J.E., Smith, M.A., Bickel, J.E., & Bickel, J.E. (2021). Optimizing Machine Learning Predictions with Prediction Uncertainty [Conference Poster]. https://doi.org/10.2172/1860307

Volkova, S., Stracuzzi, D.J., Shafer, J., Ray, J., Pullum, L., & Pullum, L. (2021). Robustness and Validation of Model and Digital Twins Deployment. https://doi.org/10.2172/1770631

Stracuzzi, D.J. (2021). Preliminary Work on a Digital Twin for Cancer Patients [Conference Presenation]. https://doi.org/10.2172/1854684

Peterson, M.G., Stracuzzi, D.J., Young, C.J., Vollmer, C., Brogan, R., & Brogan, R. (2020). Generating Uncertainty Distributions for Seismic Signal Onset Times. Bulletin of the Seismological Society of America, 111(1), pp. 11-20. https://doi.org/10.1785/0120200125

Stracuzzi, D.J. (2020). Models of Models: Recognizing and Managing the Uncertainties of Machine Learning in Engineering Applications [Conference Presenation]. https://doi.org/10.2172/1831563

Stracuzzi, D.J., Speed, A., & Speed, A. (2020). Research Needs for Trusted Analytics in National Security Settings [Presentation]. https://www.osti.gov/biblio/1832675

Stracuzzi, D.J., Speed, A., & Speed, A. (2020). Research Needs for Trusted Analytics in National Security Settings. https://doi.org/10.2172/1662023

Peterson, K., Powell, A.J., Tezaur, I.K., Roesler, E.L., Nichol, J.J., Peterson, M.G., Davis, W.L., Jakeman, J.D., Stracuzzi, D.J., Bull, D.L., & Bull, D.L. (2020). Arctic Tipping Points Triggering Global Change (LDRD Final Report). https://doi.org/10.2172/1669210

Stracuzzi, D.J., Peterson, M.G., Popoola, G.A., & Popoola, G.A. (2020). Measuring and Extracting Activity from Time Series Data. https://doi.org/10.2172/1673451

Nichol, J.J., Peterson, M.G., Peterson, K., Stracuzzi, D.J., Fricke, M., & Fricke, M. (2020). Machine Learning to Compare Arctic Simulations With Observed Data [Conference Poster]. https://www.osti.gov/biblio/1807391

Jones, S.T., Stracuzzi, D.J., Vollmer, C., & Vollmer, C. (2020). Improving Object Classifier Performance Using a Pattern of Life [Conference Poster]. https://www.osti.gov/biblio/1766666

Gooding, R.L., Draayer, E.C., McMahon, N.D., Stracuzzi, D.J., Anderson, D.Z., & Anderson, D.Z. (2020). Identifying and Clustering Activity in Seismic Waveforms [Conference Poster]. https://www.osti.gov/biblio/1765312

Popoola, G.A., Peterson, M.G., Stracuzzi, D.J., & Stracuzzi, D.J. (2020). Using Anomaly Detection for Activity Identification [Conference Poster]. https://www.osti.gov/biblio/1882050

Nichol, J.J., Peterson, M.G., Peterson, K., Stracuzzi, D.J., & Stracuzzi, D.J. (2020). Comparing Simulated and Observed Data with Random Forest Feature Importance [Conference Poster]. https://www.osti.gov/biblio/1766757

Darling, M.C., Hush, D.R., Stracuzzi, D.J., & Stracuzzi, D.J. (2020). A Novel Measure of Uncertainty For Machine Learning Predictions [Conference Poster]. https://www.osti.gov/biblio/1768156

Nichol, J.J., Peterson, M.G., Peterson, K., Stracuzzi, D.J., Fricke, M., Moses, M., & Moses, M. (2019). FEATURE COMPARISON OF ARCTIC OBSERVATIONS AND CLIMATE MODELS [Conference Poster]. https://www.osti.gov/biblio/1643593

Kramer, S., Bolintineanu, D.S., Long, K., Waymel, R., Quintana, E.C., Jones, R.E., Roberts, S.A., Newcomer, J.T., Stracuzzi, D.J., Swiler, L.P., & Swiler, L.P. (2019). Mechanics of Materials Utilizing Machine Learning: Examples at Sandia National Laboratories [Conference Poster]. https://www.osti.gov/biblio/1643105

Stracuzzi, D.J. (2019). What is Machine Learning? [Presentation]. https://www.osti.gov/biblio/1645912