Hello, everyone. I am currently a postdoctoral researcher at the HKUST Business School, Hong Kong University of Science and Technology (HKUST), working with Prof. Dongwook Shin. I earned my Ph.D. from the Department of Mathematical Sciences at Korea Advanced Institute of Science and Technology (KAIST) in August 2021. My PhD advisor was Prof. Kyoung-Kuk Kim, a professor in the College of Business, KAIST.
[Curriculum Vitae] (Last update: Jan 7th, 2025)
E-mail : thk5594 AT gmail DOT com or taeho AT ust DOT hk
I would welcome an opportunity to serve as a reviewer. Please don't hesitate to send me the request.
RGC Junior Research Fellow Scheme (JRFS) 2025-2026, Hong Kong Research Grant Council (RGC)
Project title: Reinforcement Learning with High-Dimensional Feature (Supervisor: Dr. Dongwook SHIN)
Award amount: HKD 420,000 per year
Ph.D., Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Sep. 2015 - Aug. 2021
(Thesis title: Data-driven simulation modeling, uncertainty quantification, and optimization)
B.Sc., Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Feb. 2011 - Aug. 2015
Monte Carlo methods in operations research and operations management
Sequential decision making under uncertainty
Data-driven stochastic modeling and simulation analytics
Advanced statistical methods in stochastic simulation
A Reduced Form Approach to Strategic Liquidity Provision in Automated Market Making
working paper
with Kyoung-Kuk Kim and Donghwa Seo
Data-Driven Sequential Sampling for Tail Risk Mitigation [arxiv]
submitted
with Dohyun Ahn
Ensemble Copula Coupling for Multivariate Input Modeling and Uncertainty Quantification
Major Revision at Mathematics of Operations Research
with Kyoung-Kuk Kim and Michael C. Fu
Optimizing Input Data Collection for Ranking and Selection [arxiv]
Major Revision at Operations Research
with Eunhye Song
Optimizing Input Data Acquisition for Ranking and Selection: A View through the Most Probable Best [link]
Proceedings of the 2022 Winter Simulation Conference
with Eunhye Song
Rate-Optimal Budget Allocation for the Probability of Good Selection [link]
Finalist, Best Contributed Theoretical Paper, WSC 2024
Proceedings of the 2024 Winter Simulation Conference
with David J. Eckman
Risk-Sensitive Ordinal Optimization [link]
Proceedings of the 2023 Winter Simulation Conference
with Dohyun Ahn
Operations Research, Articles in Advance
with Kyoung-Kuk Kim and Eunhye Song
Selection of the Most Probable Best under Input Uncertainty [link]
Proceedings of the 2021 Winter Simulation Conference
with Kyoung-Kuk Kim and Eunhye Song
Optimizing input data collection for ranking and selection, INFORMS Annual Meeting, Atlanta, GA, Oct 2025 (scheduled)
Optimizing input data collection for ranking and selection, INFORMS International Meeting, Singapore, July 2025
Optimizing input data collection for ranking and selection, Department Seminar, UNIST IE, Mar 2025
Optimal input uncertainty reduction for ranking and selection, POMS-HK 2025, Hong Kong, Jan 2025
Optimal selection of financial strategies for tail risk mitigation, INFORMS Annual Meeting 2023, Phoenix, AZ.
Selection of the most probable best, INFORMS Annual Meeting 2022, Indianapolis, IN.
Data-driven stochastic modeling and uncertainty quantification via Ensemble Copula Coupling, OR Colloquium, Penn State IME, 2022
Selection of the most probable best under input uncertainty, 2021 Winter Simulation Conference, Phoenix, AZ.
Input-output analysis of high-dimensional stochastic systems, INFORMS Annual Meeting 2020, Virtual.
Multivariate input modeling and uncertainty quantification via Ensemble Copula Coupling, INFORMS Annual Meeting 2019, Seattle, WA.