Health Information
Discovery & Evidence Lab
We uncover evidence hidden in complex health data.
Statistical thinking connects our methods to real-world questions.
Chungbuk National University · Information and Statistics
01 / ABOUT THE LAB
Discovering hidden evidence in complex health data.
Health data bring together missing values, measurement error, individual differences, and changes over time. We develop statistical methods that account for these complexities.
Grounded in missing data analysis and causal inference, our research spans clinical and public health data, wearable signals, and streaming data. We value valid estimation, uncertainty quantification, and interpretability alongside predictive performance.
02 / RESEARCH
01
MISSING DATA & ROBUST INFERENCE
Developing imputation and estimation methods for reliable inference from incomplete data.
Multiple imputation
Robust estimation
02
CAUSAL INFERENCE & EVIDENCE SYNTHESIS
Estimating causal effects and integrating evidence across studies and populations.
Causal effects
Population-adjusted comparisons
Meta-analysis
03
LONGITUDINAL & STREAMING DATA
Developing statistical methods for repeated measurements and continuously arriving data.
Longitudinal models
Online estimation
Streaming imputation
04
DIGITAL HEALTH & BIOSTATISTICS
Understanding health and disease through clinical, wearable, and population health data.
Wearable data
Measurement error
Clinical & public health