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Center for Computing Research

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Publication	Type	Year
Deep Neural Networks as Surrogates for Intractable Constraints and Problem Dimension Reduction: SC ACOPF AIChE Annual Meeting Zachary Kilwein, Jordan Heath Jalving, Logan Blakely, Michael Shannon Eydenberg, Carl Laird, Fani Boukouvla	Conference Presentation – 2022 Conference Presentation	2022
Verification of Neural Network Surrogates Escape 32 Joshua Haddad, Michael Lee Bynum, Michael Shannon Eydenberg, Logan Blakely, Zachary Kilwein, Fani Boukouvala, Laird Carl, Jordan Heath Jalving	Conference Paper – 2021 Conference Paper	2021
Physics-Informed Machine Learning Surrogates with Optimization-Based Guarantees: Applications to AC Power Flow AIChE Annual Meeting Jordan Heath Jalving, Michael Shannon Eydenberg, Logan Blakely, Zachary Kilwein, Fani Boukouvala, Carl Laird	Conference Presentation – 2021 Conference Presentation	2021
Toward Future Energy Generation Systems: Multi-Scale Optimization with Market Interactions AIChE Annual Meeting Jordan Heath Jalving, Jaffer Ghouse, Ben Knueven, Shawn Martin, Nicole Cortez, Gao Xian, John Daniel Siirola, David Miller, Alexander Dowling	Conference Presentation – 2021 Conference Presentation	2021
Integration of Optimization and Machine Learning for Improving Electrical Grid Operation INFORMS Annual Meeting Carl Laird, Jordan Heath Jalving, Logan Blakely, Michael Shannon Eydenberg, Fani Boukouvala, Zachary Kilwein	Conference Presentation – 2021 Conference Presentation	2021
A Critique of Optimization Modeling Environments for Complex Engineered Systems Workshop on Computational and Mathematical Challenges in Complex Engineering Systems William Eugene Hart, Carl Damon Laird, John Daniel Siirola, Bethany L. Nicholson, Jordan Heath Jalving, Michael Lee Bynum	Conference Presentation – 2021 Conference Presentation	2021
Graph-Based Modeling and Optimization using Plasmo.jl INFORMS Annual Meeting Jordan Heath Jalving	Conference Presentation – 2021 Conference Presentation	2021
Deep Neural Network as Surrogates for Intractable Constraints and Problem Dimension Reduction: Security Constrained AC Optimal Power Flow American Institute of Chemical Engineering Annual Meeting 2021 Zachary Alexander Kilwein, Logan Blakely, Michael Shannon Eydenberg, Jordan Heath Jalving, Carl Damon Laird, Fani Boukouvala	Abstract – 2021 Abstract	2021
AC-Optimal Power Flow Solutions with Security Constraints from Deep Neural Network Models 31st European Symposium on Computer-Aided Process Engineering (ESCAPE-31) Zachary Kilwein, Fani Boukouvala, Carl Damon Laird, Anya Castillo, Logan Blakely, Michael Shannon Eydenberg, Jordan Heath Jalving, Lisa Batsch-Smith	Conference Paper – 2021 Conference Paper	2021
Scalable Parallel Nonlinear Optimization with PyNumero and Parapint SIAM Conference on Optimization (OP21) Michael Lee Bynum, Santiago Rodriguez, Carl Damon Laird, Bethany L. Nicholson, Jordan Heath Jalving, John Daniel Siirola, Denis Ridzal	Conference Presentation – 2021 Conference Presentation	2021
Physics-Informed Machine Learning Surrogates with Optimization-Based Guarantees: Applications to AC Power Flow 2021 AIChE Annual Meeting Jordan Heath Jalving	Abstract – 2021 Abstract	2021
Parapint: Scalable Parallel Solution of Structured Nonlinear Programs 2021 AIChE Annual Meeting Michael Lee Bynum, Santiago Rodriguez, Carl Damon Laird, Bethany L. Nicholson, Jordan Heath Jalving, John Daniel Siirola, Denis Ridzal	Abstract – 2021 Abstract	2021
Unraveling and Exploiting Complex Structures in Optimization Using OptiGraphs AIChE Virtual Annual Meeting 2020 Jordan Heath Jalving, Sungho Shin, Victor M. Zavala https://www.osti.gov/search/identifier:1829232	Conference Presentation – 2020 Conference Presentation	2020
Document Title	Type	Year