2011. 9 ~ 2019. 5, Ph.D. in Mathematics (minor in computer science), University of Wisconsin-Madison, USA
2008. 3 ~ 2011. 2, B.S. in Mathematics, POSTECH, Korea

2023 ~ current, Assistant Professor, SeoulTech, Korea
2022 ~ 2023, Assistant Professor, Gachon University, Korea
2021 ~ 2022, BK21 postdoctoral Researcher, Seoul National University, Korea
2019 ~ 2021, Staff Engineer, Samsung Electronics, Korea

Y. Kim, Well-posedness for constrained Hamilton-Jacobi equations, Acta Applicandae Mathematicae, 2020

Y. Kim, H. V. Tran, S. N.T. Tu, State-constraint static Hamilton-Jacobi equations in nested domains, SIAM Journal on Mathematical Analysis, 2020

Y. Kim, I. Yang, On Representation Formulas for Optimal Control: A Lagrangian Perspective, IET Control Theory & Applications, 2022

Y. Kim, I. Yang, K. Jun, Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs, Advances in Neural Information Processing Systems (NeurIPS), 2022

Y. Kim, Well-posedness for constrained Hamilton-Jacobi equations, Acta Applicandae Mathematicae, 2020

Y. Kim, On uniqueness for one-dimensional constrained Hamilton-Jacobi equation, Minimax Theory and its Applications, 2020

Y. Kim, H. V. Tran, S. N.T. Tu, State-constraint static Hamilton-Jacobi equations in nested domains, SIAM Journal on Mathematical Analysis, 2020

J. Shin, A. Hakobyan, M. Park, Y. Kim, G. Kim, I. Yang, Infusing model predictive control into meta-reinforcement learning for mobile robots in dynamic environments, IEEE Robotics and Automation Letters, 2022

Y. Kim, I. Yang, On Representation Formulas for Optimal Control: A Lagrangian Perspective, IET Control Theory & Applications, 2022

Y. Kim, I. Yang, K. Jun, Improved Regret Analysis for Variance-Adaptive Linear Bandits and Horizon-Free Linear Mixture MDPs, Advances in Neural Information Processing Systems (NeurIPS), 2022

Y. Kim, K. Kim, I. Yang, On Stabilizability-Independent Asymptotic Concentration Bounds for Bayesian Identification of Linear Non-Gaussian Systems, IEEE Control Systems Letters (under review)

Y. Kim, K. Kim, I. Yang, Learning Linear-Quadratic Regulators via Thompson Sampling with Langevin Dynamics, preprint

Kwon, G. Montufar, I. Yang, Y. Kim †, Training Wasserstein GANs without gradient penalties, preprint

선도센터(SRC), 참여연구원, 2023-2030
생애첫연구 (NRF), PI, 2023-2026