A framework for baseline load estimation in demand response: Data mining approach. - Saehong Park; Seunghyoung Ryu; Yohwan Choi; Hongseok Kim (SmartGridComm, 2014)

Hybrid electrochemical modeling with recurrent neural networks for li-ion batteries. - Saehong Park; Dong Zhang 011; Scott J. Moura (ACC, 2017)

Optimal Input Design for Parameter Identification in an Electrochemical Li-ion Battery Model. - Saehong Park; Dylan Kato; Zach Gima; Reinhardt Klein; Scott J. Moura (ACC, 2018)

Distributionally Robust Surrogate Optimal Control for Large-Scale Dynamical Systems. - Aaron Kandel; Saehong Park; Hector Eduardo Perez; Geumbee Kim; Yohwan Choi; Hyoung Jun Ahn; Won Tae Joe; Scott J. Moura (ACC, 2020)

Reinforcement Learning-based Fast Charging Control Strategy for Li-ion Batteries. - Saehong Park; Andrea Pozzi; Michael Whitmeyer; Hector Eduardo Perez; Won Tae Joe; Davide Martino Raimondo; Scott J. Moura (CCTA, 2020)

Optimal Control of Battery Fast Charging Based-on Pontryagin's Minimum Principle. - Saehong Park; Donggun Lee; Hyoung Jun Ahn; Claire J. Tomlin; Scott J. Moura (CDC, 2020)

Reinforcement Learning-based Fast Charging Control Strategy for Li-ion Batteries. - Saehong Park; Andrea Pozzi; Michael Whitmeyer; Won Tae Joe; Davide Martino Raimondo; Scott J. Moura (CoRR, 2020)

Estimation of Cyclable Lithium for Li-ion Battery State-of-Health Monitoring. - Saehong Park; Dong Zhang 011; Reinhardt Klein; Scott J. Moura (ACC, 2021)

Faster and Healthier Charging of Lithium-Ion Batteries via Constrained Feedback Control. - Luis D. Couto; Raffaele Romagnoli; Saehong Park; Dong Zhang 011; Scott J. Moura; Michel Kinnaert; Emanuele Garone (IEEE Trans. Control. Syst. Technol., 2022)

Reinforcement Learning Versus PDE Backstepping and PI Control for Congested Freeway Traffic. - Huan Yu; Saehong Park; Alexandre M. Bayen; Scott J. Moura; Miroslav Krstic (IEEE Trans. Control. Syst. Technol., 2022)

Distributionally Robust Surrogate Optimal Control for High-Dimensional Systems. - Aaron Kandel; Saehong Park; Scott J. Moura (IEEE Trans. Control. Syst. Technol., 2023)