BIOGRAPHY

Mr. Wilus is a master’s level biostatistician who provides statistical support to investigators across campus as part of Meharry Medical College’s Biostatistics Core. He has introduced new correlation and similarity measures, which have been used to analyze roughly 13,909 genes and identify the most significant gene responsible for Williams Syndrome; a new TWW Growth model to analyze qPCR data; as well as a new machine learning method to analyze binary, multinomial, and ordinal data. Each method introduced has a corresponding publicly available R package he wrote that has been tested and approved by CRAN. These methods have applications in public and global health, epigenetics, epigenomics, data science, cancer research, and medical imaging. He is involved in studying the implementation of HIV testing and linkage to treatment or prevention among vulnerable populations, reproductive health in women who experience sexual violence, HIV/HCV co-infection in patients, diabetes medical nutrition therapy in African American women, synthetic opioid overdose death rates in the United States, and investigating the leading causes of death in vulnerable populations in Tennessee.