Jake Roth

rothjakem@gmail.com

I'm a post-doc in the School of Statistics at the University of Minnesota where I'm fortunate to work with Dr. Eric Chi. Previously, I was a PhD student in ISyE (also at UMN) where I worked on computational risk-averse problems with Dr. Ying Cui and distributionally robust optimization with Dr. Louis Chen. Before that, I studied rare events in power networks with Dr. Mihai Anitescu as a pre-doc at Argonne National Laboratory and image reconstruction problems with Dr. Emil Sidky as a statistics MS student at the University of Chicago. And long(er) ago, I was an undergrad at Claremont McKenna College.

Currently, I'm interested optimization problems involving uncertainty.

Preprints

Perturbation Duality for Robust and Distributionally Robust Optimization: Short and General Proofs
Louis L. Chen, Jake Roth, Johannes O. Royset
arXiv:math.oc, 2026
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Journal Articles

Fast Computation of Superquantile-Constrained Optimization Through Implicit Scenario Reduction
Jake Roth, Ying Cui
Journal of Machine Learning Research, 2025
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On O(n) Algorithms for Projection onto the Top-k-sum Sublevel Set
Jake Roth, Ying Cui
Mathematical Programming Computation, 2025
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Failure Probability Constrained AC Optimal Power Flow
Anirudh Subramanyam, Jake Roth, Mihai Anitescu
IEEE Transactions on Power Systems, 2023
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A Kinetic Monte Carlo Approach for Simulating Cascading Transmission Line Failure
Jake Roth, David A. Barajas-Solano, Panos Stinis, Jonathan Weare, Mihai Anitescu
SIAM Multiscale Modeling and Simulation, 2021
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Conference Proceedings

Parameter selection with the Hotelling observer in linear iterative image reconstruction for breast tomosynthesis
Sean D. Rose, Jake Roth, Cole Zimmerman, Ingrid Reiser, Emil Y. Sidky, Xiaochuan Pan
SPIE, 2018
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March 2026 (INFORMS Optimization Society) Circumventing Compactness in Conditional-Moment Optimal Transport Duality: A Perturbation Approach | pdf
July 2025 (ICCOPT) Using Sparsity in Superquantile-Constrained Optimization | pdf
March 2021 (SIAM CSE 2021, Invited) Computational methods for rare events in power systems
August 2020 (MACSER Optimization Series) Cascade-constrained optimal power flow | pdf
March 2020 (SIAM UQ 2020, Invited) Distribution of cascading power network failure severity
February 2020 (UChicago Lunch Seminar) Conjugate gradients tutorial | pdf
April 2019 (ANL LANS Seminar) Cascading failures and energy landscapes for power systems | pdf
May 2018 (UChicago MS Presentation) Toy model for distributionally robust optimization | pdf

Claremont McKenna College

2009 - 2013

University of Chicago

2016 - 2018

MCS @ Argonne

2018 - 2020

University of Minnesota

2020 - Present

Source: thanks to Sebastin Santy for the theme.