(734) 764-6585

Bioinformatics, Clinical Research, Healthcare Management and Outcomes, Precision Medicine
Bayesian Methods, Causal Inference, Heterogeneous Data Integration, High-Dimensional Data Analysis, Longitudinal Data Analysis, Machine Learning, Optimization, Predictive Modeling, Statistical Inference, Statistical Modeling

Nicholas Henderson

Assistant Professor



Rogel Cancer Center

My research primarily focuses on the following main themes: 1) development of methods for risk prediction and analyzing treatment effect heterogeneity, 2) Bayesian nonparametrics and Bayesian machine learning methods with a particular emphasis on the use of these methods in the context of survival analysis, 3) statistical methods for analyzing heterogeneity in risk-benefit profiles and for supporting individualized treatment decisions, and 4) development of empirical Bayes and shrinkage methods for high-dimensional statistical applications. I am also broadly interested in collaborative work in biomedical research with a focus on the application of statistics in cancer research.