Chul Ahn

Chul Ahn is a Professor at the University of Texas Southwestern Medical Center’s School of Public Health and Director of the Biostatistics Shared Resource at the Simmons Comprehensive Cancer Center. He holds a PhD in Statistics from Carnegie Mellon University (1986) and has extensive experience in biostatistical research, including over 500 peer-reviewed publications. His work focuses on clinical trial design, analysis of correlated outcomes (e.g., repeated measurements, clustered data), and methodological advancements in sample size calculations for various study designs. Dr. Ahn has served on numerous NIH, CDC, and DoD grant review panels and led the Biostatistics and Data Management Core for NIH-funded initiatives like SCCOR, SPORE, and multi-center studies. His research interests include pragmatic trial design, cluster randomized trials, and oncology-related statistical methodologies.

Education: MS in Operations Research (Georgia Tech, 1982), MS and PhD in Statistics (Carnegie Mellon, 1986). Previous roles include faculty positions at Albert Einstein College of Medicine and University of Texas Medical School at Houston.

Research Interests: Clinical trials methodology, correlated data analysis, sample size determination for complex designs, and applications in oncology and public health. His work bridges statistical theory and practical clinical challenges, emphasizing rigorous methodologies for improving healthcare outcomes.

Publications Trends: Over 500+ articles, with a focus on biostatistical methods for clinical trials, clustered data, and oncology trials. Recent work addresses pragmatic trial design, stepped-wedge cluster trials, and biomarker-driven cancer research. His methodological contributions include sample size formulas for historical controls, split-mouth designs, and longitudinal studies with missing data.

Awards: While specific honors are not listed, his leadership roles and NIH-funded projects reflect significant recognition in the field.

Labs/Teams: Leads the Biostatistics Shared Resource at Simmons Comprehensive Cancer Center, supporting translational and clinical research through advanced statistical methodologies.