Current Role
Graduate Research Assistant
Bayesian Inference Lab, Inha University
Curriculum Vitae
M.S. Student in Statistics & Data Science at Inha University
I work on Bayesian machine learning, uncertainty quantification, molecular toxicity prediction, and time-series anomaly detection. My recent research focuses on reliable probabilistic modeling for sensor, molecular, and domain-informed prediction problems.
Current Role
Graduate Research Assistant
Bayesian Inference Lab, Inha University
Research Focus
Bayesian ML & Uncertainty Quantification
Probabilistic modeling for sensor, molecular, and time-series data
Output
4 Publications · 3 Talks · 1 Patent
Molecular modeling, Bayesian optimization, time-series analysis, and domain-informed learning
Highlights
4 Awards
AI challenge, hackathon, conference paper, and project recognition
01
Academic background in statistics, data science, and software convergence.
Feb. 2025 - Feb. 2027 (expected)
Bayesian Inference Lab, advised by Seongil Jo.
Mar. 2019 - Jul. 2023
Interdisciplinary major in Samsung Convergence Software Course.
02
Research positions spanning Bayesian statistics, HCI, and deployable AI systems.
Feb. 2025 - Present
Sep. 2023 - Jul. 2024
Jul. 2024 - Feb. 2025
03
Publications, presentations, and intellectual property across applied AI and statistical modeling.
Publication
Applied Sciences, Aug. 2025
Publication
Journal of the Korea Institute of Intelligent Transport Systems, Feb. 2024
Journal of Cheminformatics, May 2026
Computational Statistics, May 2026
Presentations
Patent
Patent No. 10-2024-2864144
Filing title: AI-based movement path prediction system for search and rescue operations.
04
Recognition across research, competition, and conference settings.
2025
Grand Award, Inha University AI Convergence Research Center
2025
Finalist, 7th place
2024
Anomaly Detection in Driving Patterns Using Contrastive Learning, 2023 ITS Korea Fall Conference
2023
Road Surface Detection System Using Smartphone Accelerometer Sensors, Fall 2023 VIP Presentation
05
Tooling and modeling stack for statistical research and machine learning systems.