CV
Please find my full CV here.
Education
- Ph.D in Industrial and Management Engineering, Korea University, 2022
- B.S. in Industrial and Management Engineering, Korea University, 2016
Work experience
- Postdoctoral Researcher, Apr. 2022 ~ Present
- H. Milton Stewart School of Industrial and Systems Engineering
- Artificial Intelligence for Medical Data Analysis and Integration for Clinical Usage
- Supervisor: Prof. Jing Li
- Graduate Research Assistant, Mar. 2016 ~ Feb. 2022
- Industrial and Management Engineering, Korea University
- Work in various research projects to solve real-world industrial problems
- Supervisor: Prof. Seoung Bum Kim
Awards & Honors
- Research Funding, Next-Generation Science and Technology Leader NET, KOFST, 2024
- Received funding for research activities aimed at improving the logical inference capabilities of large language models.
- Best Paper Award, Finalist, IISE 2024 Data Analytics & Information Systems, 2024
- Best Paper Award, Runners-Up, INFORMS 17th Workshop on Data Mining & Decision Analytics, 2022
- SAS Best Paper Award, Korea Business Intelligence Data Mining Conference, 2018
- National Science & Technology Scholarship, Korea Student Aid Foundation, 2014 ~ 2015
- Academic Excellence Scholarship, Korea University, 2010
Skills
- Programming Languages: Python (Advanced), R (Advanced), SQL (Proficient)
- Deep Learning Frameworks: Pytorch (Advanced), Keras (Advanced), Tensorflow (Proficient)
- Tools: Git (Proficient), Docker (Intermediate)
Research Interests
- Artificial intelligence applications for medical data analysis
- Neuroimaging and cone beam computed tomography image
- Incomplete multi-modal learning with medical images
- Conditional generative artificial intelligence with diffusion models
- Interpretable graph neural networks for macromolecules
- Representation learning for out-of-distribution data
- Anomaly detection, open-set classification, and their applications
- Semi-supervised learning under class distribution mismatch scenario
- Learning with limited labeled data: semi-supervised and self-supervised learning
- Deep reinforcement learning
- Robust and feedback-efficient preference-based reinforcement learning
- Data-efficient reinforcement learning
- Large language model
- Prompt engineering for logical inference
- Automated data augmentation for self-correction
- Multi-channel signal data analysis
Publications
Selected Presentations
A Mutual Knowledge Distillation-Empowered AI Framework for Early Detection of Alzheimer’s Disease Using Incomplete Multi-Modal Images
Presentation at INFORMS 18th Workshop on Data Mining & Decision Analytics, Phoenix, Arizona, United States
Self-Supervised Contrastive Learning to Predict Alzheimer’s Disease Progression with 3D Amyloid-PET
Presentation at INFORMS 17th Workshop on Data Mining & Decision Analytics, Indianapolis, Indiana, United States
Aggregating In-Distribution Data into Positive Examples for Safe-Semi Supervised Contrastive Learning
Presentation at 2021 INFORMS Annual Meeting,
Critical Test Item Selection in Mobile Manufacturing Process
Presentation at 2021 Korean Institute of Industrial Engineers, Jeju-do, South Korea
Explainable Failure Prediction for Multi-channel Sensor Data
Presentation at 2019 INFORMS Annual Meeting, Seattle, Washington, United States
Convolutional Autoencoder-Based Multichannel Signal Monitoring Method
Presentation at 2018 INFORMS International Confererence, Taipei, Taiwan
Data-Driven Forecasting Method for Intermittent Demand
Presentation at Industrial Engineering & Management Science Conference, Seoul, Korea
Teaching
Service and leadership
- Reviewer, INFORMS Journal of Computing, 2024
- Reviewer, IEEE Transactions on Automation Science and Engineering, 2023
- Sergeant, Korean Augmentation to the United States Army, 2011.09 ~ 2013.06