About Me
I am a PhD student in Computational Science and Engineering (home unit in Aerospace Engineering) at Georgia Tech. I joined ACE group in Fall 2023 and have been working with Dr. Elizabeth Qian. Before joining the group, I received my master's in Aerospace Engineering, primarily working on surrogate modeling for engineering applications. My current research focuses on methodological development in multifidelity machine learning, leveraging both expensive high- and cheap low-fidelity data.
Education
- Georgia Institute of Technology — PhD in Computational Science and EngineeringAug 2023 – Present
- Georgia Institute of Technology — Master in Computational Science and EngineeringJan 2026 – May 2026
- Pusan National University — Master in Aerospace EngineeringSep 2020 – Aug 2022
- Pusan National University — Bachelor in Aerospace EngineeringMar 2016 – Aug 2020
Projects
All projects →
Model management strategy for hierarchical Kriging
Multifidelity Monte Carlo budget allocation strategy for hierarchical Kriging
Multifidelity Kernel Regression
Multifidelity estimator for kernel regression problem that is more robust than the single fidelity kernel regression model under the same computational budget
Error-aware digital twin of a thermal fin in heat sink systems
An error-aware digital twin that accounts for surrogate model errors during the identification process
Multifidelity Rare Event Simulation
Develop multifidelity estimators to predict the probability of failure in rare event simulation under limited computational budgets
Reliability-based design optimization of a hydrogen vessel
Reliability-based design optimization of a hydrogen pressure vessel under operating condition uncertainty via a parametrized component-based reduced basis model
Statistical Fatigue Life Prediction of a Damaged Structure Using Reduced Basis Digital Twin
Digital twin-driven fatigue life prediction of a defected hydrogen pressure vessel based on rapid yet accurate defect size diagnosis
Publications
All publications →- Condition-based fatigue life monitoring of a high-pressure hydrogen storage vessel using a reduced basis digital twin Engineering Structures (2025)
- Multifidelity linear regression for scientific machine learning from scarce data Foundations of Data Science (2025)
- Inverse Identification of a Constitutive Model for High-Speed Forming Simulation: An Application to Electromagnetic Metal Forming Materials (2022)
- Reliability-based Design Optimization of a High-Pressure Hydrogen Storage Vessel Using a Static Condensation Reduced Basis Element Method Transactions of the Korean Society of Mechanical Engineers, A (2022)
- On the Effect of Air-Simulated Side-Jets on the Aerodynamic Characteristics of a Missile by Multi-Fidelity Modeling Journal of the Korean Society for Aeronautical & Space Sciences (2021)
Teaching & Mentoring
Details →- Teaching Assistant — Numerical Analysis and Algorithms · Georgia Tech · Spring 2024, Spring 2025
- Teaching Assistant — Introduction to IoT-based Digital Twin · Pusan National University · Fall 2022
- Research Mentor — Multifidelity Neural Network Project (PURA) · Fall 2024 – Fall 2025
- Research Mentor — Multifidelity Linear Regression Project (SURE) · Summer 2025