|Ph.D.,||Rensselaer Polytechnic Institute,||(2022)|
|M.S.,||University of Connecticut,||(2018)|
|B.S.,||University of Connecticut,||(2017)|
With the rise of big data ecosystems, high throughput genotyping, and the emergence of AI technologies, the future of medicine is poised to radically change. Personalized biomarker profiles have considerable potential in the degree to which it will be possible to not only diagnose complex disease, but also ascertain potential treatment pathways.
Thus, the primary aim of my work is to develop a more robust understanding of the relationship between individual patient informatics and disorder pathology. Specifically, the focus of my research is utilizing a computational approach to understanding and diagnosing autism spectrum disorder (ASD). As ASD is a fairly heterogenous condition with several co-occurring conditions, utilizing and developing methods for best assessing individualized patient data for diagnostic and clinical elucidation objectives holds considerable promise.