Innyoung Kim

Course: Integrated M.S.-Ph.D. Program
Research Topic: Automation and optimization of computational fluid dynamics using deep reinforcement learning
Contact: innykim at postech.ac.kr
Member since March 2020

1. Publications

Kim, I., & You, D. “Fluid dynamic control and optimization using deep reinforcement learning.” JMST Advances, 1-5, 2024.
Kim, I., Kim, S., & You, D. “Non-iterative generation of an optimal mesh for a blade passage using deep reinforcement learning.” Computer Physics Communications, 108962, 2024.
Kim, I., Yoon, D., Jeong, J., Kim, S., & You, D. “Domain reduction strategy for large-eddy simulation to predict underwater radiated noise from a marine propeller.” Ocean Engineering, 279, 114538, 2023.
Kim, S.*, Kim, I.*, & You, D. “Multi-condition multi-objective optimization using deep reinforcement learning.” Journal of Computational Physics, vol. 462, 111263, 2022.
Jeong, J., Kim, I., Yoon, D. & You, D. “Numerical Analysis of Underwater Radiated Noise Over a Marine Propeller.” Journal of Computational Fluids Engineering, 2021.

2. Presentations

Kim, I., Kim, S. & You, D. (2023). Toward automatic CFD of flow through a blade passage using deep reinforcement learning. 76th Annual Meeting of the Division of Fluid Dynamics, American Physical Society.
Kim, I., Kim, S. & You, D. (2022). Automatic mesh generation for blades using deep reinforcement learning. The 12th National Congress on Fluids Engineering, June 22-24, Changwon, Korea.

3. Awards

Kim, I. “BK21+ best paper award”, the Department of Mechanical Engineering at Pohang University of Science and Technology (POSTECH), December 6, 2023
Kim, I. “BK21+ best paper award”, the Department of Mechanical Engineering at Pohang University of Science and Technology (POSTECH), December 13, 2022

4. Teaching (e.g. T.A.)