Selected Publications

Control and System Theory

[P2] From Optimization to Control: Quasi Policy Iteration: Amin Kolarijani and Peyman Mohajerin Esfahani
submitted for publication, November 2023, [arXiv]
[C40] Fast Approximate Dynamic Programming for Infinite-Horizon Continuous-State Markov Decision Processes: Amin Kolarijani, Gyula Max, and P. Mohajerin Esfahani
Neural Information Processing Systems (NeurIPS), December 2021, [Link], [arXiv], [Code]
Journal version: [J35], [arXiv], [Code]
[J24] Macroscopic Noisy Bounded Confidence Models with Distributed Radical Opinions: Amin Kolarijani, Anton Proskurnikov, and Peyman Mohajerin Esfahani
IEEE Transactions on Automatic Control (TAC), vol. 66, no. 3, pp. 1174-1189, 2021, [Link], [arXiv]
[J5] A Tractable Fault Detection and Isolation Approach for Nonlinear Systems with Probabilistic Performance: Peyman Mohajerin Esfahani and John Lygeros
IEEE Transactions on Automatic Control (TAC), vol. 61, no. 3, pp. 633-647, March 2016, [Link], [arXiv]

[J23] Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator: Viet Anh Nguyen, Daniel Kuhn, and Peyman Mohajerin Esfahani
Operations Research (OR), vol. 70, no. 1, pp. 490-515, 2021, [Link], [arXiv], [Code]
>> Winner of the 2018 George Nicholson Outstanding Student Paper
[J14] From Infinite to Finite Programs: Explicit Error Bounds with an Application to Approximate Dynamic Programming: Peyman Mohajerin Esfahani, Tobias Sutter, Daniel Kuhn, and John Lygeros
SIAM Journal on Optimization (SIOPT), vol. 28, no. 3, pp. 1968-1998, July 2018, [Link], [arXiv]
[J15] Data-driven Distributionally Robust Optimization Using the Wasserstein Metric: Performance Guarantees and Tractable Reformulations: Peyman Mohajerin Esfahani and Daniel Kuhn
Mathematical Programming, vol. 171, pp. 115-166, September 2018, [Link], [arXiv]
>> The 2020 INFORMS Frederick W. Lanchester Prize
>> MOSEK Jupyter Notebook and Video
[J3] Performance Bounds for the Scenario Approach and an Extension to a Class of Non-convex Programs: Peyman Mohajerin Esfahani, Tobias Sutter, and John Lygeros
IEEE Transactions on Automatic Control (TAC), vol. 60, no. 1, pp. 46-58, January 2015, [Link], [arXiv]
>> The 2016 George S. Axelby Outstanding Paper Award

[J44] Learning in Inverse Optimization: Incenter Cost, Augmented Suboptimality Loss, and Algorithms: Pedro Zattoni Scroccaro, Bilge Atasoy, and Peyman Mohajerin Esfahani
Operations Research (OR), 2024, [Link], [arXiv], [Code]
[J34] Adaptive Online Optimization with Predictions: Static and Dynamic Environments: Pedro Zattoni Scroccaro, Arman Sharifi Kolarijani, and Peyman Mohajerin Esfahani
IEEE Transactions on Automatic Control (TAC), vol. 68, no. 5, pp. 2906-2921, May 2023, [Link], [arXiv]
[C39] Principal Component Hierarchy for Sparse Quadratic Programs: Robbie Vreugdenhil, Viet Anh Nguyen, Armin Eftekhari, Peyman Mohajerin Esfahani
International Conference on Machine Learning (ICML), Vienna, Austria, July 2021, [arXiv], [Code]
[J31] Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization: Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh, Daniel Kuhn, and Peyman Mohajerin Esfahani
Mathematics of Operations Research (MOR), vol. 48, no. 1, pp. 1-37, 2023, [Link], [arXiv]