(734) 764-6585

Applications:
Bioinformatics, Clinical Research, Healthcare Management and Outcomes, Precision Medicine
Methodologies:
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

Biostatistics


Affiliation(s):

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.