Faculty Profile
Bret Hanlon, PhD (he/him)
- Associate Director of Clinical Trials, SABER
- Research Associate Professor, Department of Biostatistics
Bret Hanlon, PhD, is a biostatistician with deep expertise in the design and analysis
of clinical trials, health services research, and high-dimensional data analysis.
Most recently a Scientist III in the Clinical Trials Program at the University of
Wisconsin–Madison’s Department of Biostatistics and Medical Informatics, Dr. Hanlon
served as a principal investigator and lead statistician on numerous industry- and
federally funded studies, including large-scale trials in oncology, cardiology, and
population health. His collaborative work spanned academic medicine and independent
statistical oversight for pharmaceutical trials. Trained at Cornell (PhD) and Harvard
(postdoc), his methodological contributions encompass Bayesian modeling, branching
processes, and regularized regression, with applications published across biostatistics,
surgery, and health outcomes research.
- PhD, Cornell University, 2009
- MS, Texas Tech University, 2005
- BS, University of North Carolina, 2003
Dr. Hanlon’s research interests span both methodological development and applied statistical
collaboration in biomedical and health services research. Methodologically, he focuses
on high-dimensional inference, robust estimation techniques, branching processes with
random effects, and regularized ordinal regression—developing tools to address challenges
such as clustered and censored longitudinal data, informative visitation, and outcome
heterogeneity. His applied interests center on clinical trial design, particularly
cluster- and stepped-wedge randomized trials, and analytic support for independent
data monitoring in multi-site industry-sponsored studies. He has worked extensively
in oncology, cardiology, bariatric surgery, and critical care, with recent projects
using machine learning for risk prediction and scenario planning to guide end-of-life
decision-making. His work also contributes to implementation science and the evaluation
of shared decision-making interventions in surgical care.
Areas of Expertise: Aging, Biostatistics, Cancer, Cardiovascular Health, Clinical Trials, Health Care, Health Informatics, Modeling, Women’s Health