Machine Learning and Optimization Lab.
Career History
- 2012: B.S. Industrial Engineering, KAIST
- 2014: M.S. Industrial Engineering, KAIST
- 2019: Ph.D. Industrial Engineering, KAIST
- 2019-2020: Data Scientist, Samsung Fire & Marine Insurance, Seoul
- 2020-2022: Marie Sklodowska-Curie Fellow, School of Mathematics, The University of Edinburgh, UK
- 2022-Present: Assistant Professor, Industrial Engineering, UNIST
- 2024.6-2024.8: Visiting Researcher, Alan Turing Institute, London, UK
Intro
Machine Learning and Optimization Lab. conducts research on the theory and methodology of optimization and machine learning, with a particular focus on stochastic optimization, inverse optimization, multi-objective optimization, and stochastic analysis. The lab develops new mathematical foundations and algorithms for modern data-driven systems, while also exploring their applications in areas such as finance, operations research, and scientific modeling. Current research topics include memory-efficient fine-tuning for large language models, physical simulation and scientific machine learning, decision-making under uncertainty, and AI-based model calibration.
Research Field
Stochastic Optimization, Multi-Objective Optimization, Inverse Optimization, Physical Simulation, Stochastic Analysis