Teresa Portone

Optimization & Uncertainty Quantification

(505) 844-4475

Sandia National Laboratories, New Mexico
P.O. Box 5800
Albuquerque, NM 87185-1327

Biography

Teresa joined Sandia in January 2020. Her research focuses on assessing and enhancing model prediction fidelity to inform high-consequence decisions for national security applications, especially in the presence of uncertainty. She has expertise in methods to characterize model-form uncertainty, sensitivity analysis, Bayesian methods, and multifidelity uncertainty quantification. She has worked on a range of applications, including disease modeling, nuclear waste repository modeling, ablation modeling for hypersonics, thermal batteries, and structural dynamics for engineered systems with bolted joints.

Education

PhD, Computational Science, Engineering and Mathematics, University of Texas at Austin, December 2019
MS, Computational Science, Engineering and Mathematics, University of Texas at Austin, May 2016
BS, Mathematics, The University of Alabama, May 2013

Publications

Dusty Brooks, Laura Swiler, Emily Stein, Paul Mariner, Eduardo Basurto, Teresa Portone, Aubrey Eckert, Rosemary Leone, (2022). Sensitivity analysis of generic deep geologic repository with focus on spatial heterogeneity induced by stochastic fracture network generation Advances in Water Resources https://doi.org/10.1016/j.advwatres.2022.104310 Publication ID: 80187

Michael Eldred, Brian Adams, Gianluca Geraci, Teresa Portone, Elliott Ridgway, John Stephens, Timothy Wildey, (2022). Deployment of Multifidelity Uncertainty Quantification for Thermal Battery Assessment Part I: Algorithms and Single Cell Results https://doi.org/10.2172/1885882 Publication ID: 80135

Erin Acquesta, Teresa Portone, Raj Dandekar, Chris Rackauckas, Rileigh Bandy, Jose Huerta, India Dytzel, (2022). Model-Form Epistemic Uncertainty Quantification for Modeling with Differential Equations: Application to Epidemiology https://doi.org/10.2172/1888443 Publication ID: 80247

Laura Swiler, Eduardo Basurto, Dusty Brooks, Aubrey Eckert, Rosemary Leone, Paul Mariner, Teresa Portone, Mariah Smith, (2022). Uncertainty and Sensitivity Analysis Methods and Applications in the GDSA Framework (FY2022) https://doi.org/10.2172/1884909 Publication ID: 80086

Teresa Portone, (2021). Computing bulk permeabilities for Task F Reference Case https://www.osti.gov/servlets/purl/1899241 Publication ID: 76695

Michael Eldred, Gianluca Geraci, Alex Gorodetsky, John Jakeman, Teresa Portone, Timothy Wildey, Ahmad Rushdi, Daniel Seidl, (2021). The Dakota Project: Connecting the Pipeline from Uncertainty Quantification R&D to Mission Impact https://www.osti.gov/servlets/purl/1891078 Publication ID: 76127

Laura Swiler, Eduardo Basurto, Dusty Brooks, Aubrey Eckert, Rosemary Leone, Paul Mariner, Teresa Portone, Mariah Smith, Emily Stein, (2021). Uncertainty and Sensitivity Analysis Methods and Applications in the GDSA Framework (FY2021) https://doi.org/10.2172/1855018 Publication ID: 79851

Teresa Portone, Erin Acquesta, Raj Dandekar, Chris Rackauckas, (2021). Learning Missing Mechanisms in a Dynamical System from a Subset of State Variable Observations https://doi.org/10.2172/1889367 Publication ID: 79360

John Jakeman, Michael Eldred, Gianluca Geraci, Teresa Portone, Ahmad Rushdi, Daniel Seidl, Thomas Smith, (2021). Multi-fidelity Machine Learning https://doi.org/10.2172/1876608 Publication ID: 79162

Merritt Michael, Gianluca Geraci, Michael Eldred, Teresa Portone, (2021). Hybrid multi-level Monte Carlo polynomial chaos method for global sensitivity analysis https://doi.org/10.2172/1882333 Publication ID: 79476

Michael Eldred, Gianluca Geraci, Alex Gorodetsky, John Jakeman, Teresa Portone, (2021). Efficient Deployment of Multifidelity Sampling Methods in Production Settings https://doi.org/10.2172/1882491 Publication ID: 79508

Erin Acquesta, Teresa Portone, (2021). Assessing the Efficacy of Universal Differential Equations to Learn Missing Dynamics from a Subset of Observable State Variables https://doi.org/10.2172/1882346 Publication ID: 79285

Teresa Portone, (2021). Multifidelity modeling for uncertainty assessment https://www.osti.gov/servlets/purl/1867791 Publication ID: 78398

Teresa Portone, (2021). Fracture statistics and integration into computational models https://www.osti.gov/servlets/purl/1869537 Publication ID: 78548

Paul Mariner, Dusty Brooks, Teresa Portone, (2021). Repository Performance Metrics and Other Quantities of Interest https://www.osti.gov/servlets/purl/1866339 Publication ID: 78295

Teresa Portone, Laura Swiler, Gianluca Geraci, Michael Eldred, (2021). Application of Multifidelity Uncertainty Quantification Methods to a Subsurface Transport Model https://doi.org/10.2172/1847219 Publication ID: 77339

Michael Eldred, Alex Gorodetsky, Gianluca Geraci, John Jakeman, Teresa Portone, (2021). Recent Advances in Adaptive Refinement of (Regression-Based) Multifidelity Surrogates for UQ https://doi.org/10.2172/1847573 Publication ID: 77372

Michael Merritt, Gianluca Geraci, Michael Eldred, Teresa Portone, (2021). Hybrid multi-level Monte Carlo polynomial chaos method for global sensitivity analysis https://doi.org/10.2172/1847581 Publication ID: 77380

Kathryn Maupin, Teresa Portone, (2021). Use of Model Discrepancy and Model Selection as a Means of Informing Missing Physics https://doi.org/10.2172/1848042 Publication ID: 77386

Teresa Portone, Rosemary Leone, (2020). Flow and Transport Modeling in Fractured Crystalline Rock Using PFLOTRAN and dfnWorks: Crystalline Task F https://www.osti.gov/servlets/purl/1833141 Publication ID: 71831

Teresa Portone, (2020). Exploring Model-Form Uncertainty in ECPMs https://www.osti.gov/servlets/purl/1818051 Publication ID: 74687

Sean DeRosa, Patrick Finley, Melissa Finley, Walter Beyeler, Daniel Krofcheck, Christopher Frazier, Laura Swiler, Teresa Portone, Erin Acquesta, Paula Austin, Drew Levin, Robert Taylor, Katherine Tremba, Monear Makvandi, Ann Hammer, Chad Davis, (2020). COVID-19 Medical Resource Demands https://www.osti.gov/servlets/purl/1807655 Publication ID: 74013

Laura Swiler, Teresa Portone, (2020). Uncertainty Analysis of a COVID-19 Medical Resource Model https://www.osti.gov/servlets/purl/1807392 Publication ID: 73743

Walter Beyeler, Christopher Frazier, Laura Swiler, Teresa Portone, Daniel Krofcheck, (2020). Treatment Model Design and Use https://www.osti.gov/servlets/purl/1783073 Publication ID: 73474

Laura Swiler, Teresa Portone, Walter Beyeler, (2020). Uncertainty analysis of Resource Demand Model for Covid-19 https://doi.org/10.2172/1630395 Publication ID: 73459

Teresa Portone, Robert Moser, (2020). Characterizing model-form uncertainty in an inadequate model of anomalous transport https://www.osti.gov/servlets/purl/1783586 Publication ID: 72858

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