Imaging and complex-structured data applications

We develop statistical models to:

  1. identify associations between complex-structured data (imaging, spatial-genomic, geospatial, digital) from multi-platform data sources,

  2. predict clinical characteristics of interest by integrating biomarkers generated from complex-structured data, and

  3. 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.

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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.

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