Graduate (Statistics and Data Science)
Research Labs
Research Lab Placement
- Conducted one month after the semester begins (early April, early October).
- Students submit a list of 1st, 2nd, and 3rd preferred professors.
- In the integrated B.A.–M.A. program, students apply in the first semester of the master’s program.
- Exception: Students awarded scholarships (e.g., GRS Scholarship, Research Assistant A) upon admission are pre-assigned to an advisor.
Research Labs
Bayesian Inference Lab
- Research on Bayesian methodology.
- Research on statistical image processing.
Advisor
Yeong-hwa Kim
E-mail
Statistical Process Monitoring (SPM) Lab
- Research on monitoring whether stochastic processes are in-control or out-of-control.
- Proposes monitoring procedures based on traditional statistical methods as well as modern machine and deep learning approaches, and evaluates their performance.
- Applications include manufacturing processes, social networks, public health and syndromic surveillance, multivariate processes, and autocorrelated processes.
Time Series Analysis and Forecasting Lab
- Research on time series analysis and forecasting.
- Studies methods for analyzing temporal data patterns and predicting future outcomes.
- Develops models applicable to economics, environment, and industry for decision-making.
Artificial Intelligence & Statistics Lab
- Conducts cutting-edge research integrating deep learning and machine learning with diverse applications such as CT/MRI-based cancer diagnosis, respiratory sound analysis, audio captioning, speaker identification, and object tracking.
- Collaborates with interdisciplinary research groups, e.g., developing deep learning platforms for chemical toxicity prediction, contributing to real-world problem-solving.
Bayesian Statistics Lab
- Research areas: Bayesian modeling, nonparametric Bayes, Bayesian additive regression trees, Bayesian networks.
- Develops new Bayesian methodologies and applies them to diagnostic accuracy, latent class models, and longitudinal data analysis in medicine, pharmacy, and finance.
Multivariate Statistics Lab
- Research on diverse methods for multivariate data analysis.
- Focus areas include functional data analysis, extreme value analysis, and quantile-based methods.
Signal Processing and Data Science Lab
- Explores AI-driven approaches across domains such as signal processing and bioinformatics, applying deep learning to propose creative problem-solving methods.
- Achieved excellent results in national and international conferences and competitions.
Biostatistics & Lifetime Data Analysis Lab
- Develops statistical methodologies for diverse research areas such as survival analysis, spatial statistics, and biostatistics.
- Conducts analysis of lifetime, spatiotemporal, and functional data.
Security & Privacy Lab
- Research on privacy-preserving machine learning and deep learning.
- Research on trustworthy machine learning and deep learning.
- Privacy-preserving optimization in finance.