Statistical methods for the analysis of complex-structured biomedical data
We develop innovative statistical methodology that leverages structural and biological information in the data. To address the challenges of handling complex-structured data, we develop and employ methods at the interface of hierarchical Bayesian modeling, variable selection, geometric/functional data analysis and spatial statistics.
Shariq Mohammed
My research interests include Bayesian modeling, variable selection, geometric functional data analysis, spatial statistics with applications to biomedical imaging data, neuro- and cancer-imaging, digital data, neurodegenerative diseases (Alzheimer’s), and precision health.