Imaging and complex-structured data applications
We develop statistical models to:
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identify associations between complex-structured data (imaging, spatial-genomic, geospatial, digital) from multi-platform data sources,
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predict clinical characteristics of interest by integrating biomarkers generated from complex-structured data, and
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understand the biological relevance and implications of our findings.
Our methods are developed in the context of various diseases such as cancer and neurodegenerative (Alzheimer’s) diseases.
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.