I am a Polymath, Solutionist, and Visionary. My research expertise is primarily in application areas requiring Machine Learning, computational methods, and high-performance computing infrastructure to provide insight into complex problems. Presently, I work in the areas of newborn screening, maternal-newborn and pediatric epidemiology, and in personalized medicine. I also have expertise in the domains bioinformatics (e.g. protein-protein interactions and binding interface predictions), analysis of autonomous vehicle-sensed data, scientometrics, and the promotion of access to information. My post-doctoral work focused on the development of a large-scale Transformer-based model for autism spectrum disorder risk screening using perinatal data from Newborn Screening Ontario and Better Outcomes Registry and Network coupled with ICES health administrative data.My doctoral thesis focused on the development of a novel semi-supervised machine learning method that applied to a very broad range of applications. I greatly enjoy mentorship of aspiring researchers and am passionate about science communication and the general promotion of algorithmic thinking, computer literacy, and access to information.