Demonstration of the relationship between sensitivity and identifiability for inverse uncertainty quantification. - Xu Wu; Koroush Shirvan; Tomasz Kozlowski (J. Comput. Phys., 2019)

Improving Intelligence of Evolutionary Algorithms Using Experience Share and Replay. - Majdi I. Radaideh; Koroush Shirvan (CoRR, 2020)

Machine learning-assisted surrogate construction for full-core fuel performance analysis. - Yifeng Che; Joseph Yurko; Koroush Shirvan (CoRR, 2021)

NEORL: NeuroEvolution Optimization with Reinforcement Learning. - Majdi I. Radaideh; Katelin Du; Paul Seurin; Devin Seyler; Xubo Gu; Haijia Wang; Koroush Shirvan (CoRR, 2021)

Rule-based reinforcement learning methodology to inform evolutionary algorithms for constrained optimization of engineering applications. - Majdi I. Radaideh; Koroush Shirvan (Knowl. Based Syst., 2021)

Pareto Envelope Augmented with Reinforcement Learning: Multi-objective reinforcement learning-based approach for Large-Scale Constrained Pressurized Water Reactor optimization. - Paul Seurin; Koroush Shirvan (CoRR, 2023)

Assessment of reinforcement learning algorithms for nuclear power plant fuel optimization. - Paul Seurin; Koroush Shirvan (Appl. Intell., 2024)

Surpassing legacy approaches and human intelligence with hybrid single- and multi-objective Reinforcement Learning-based optimization and interpretable AI to enable the economic operation of the US nuclear fleet. - Paul Seurin; Koroush Shirvan (CoRR, 2024)