Over the past two decades I’ve worked on a wide range of computational systems in both an academic and professional setting. My projects have ranged from simple data management and manipulation for billing to production-level monitoring of nationwide networking testbeds and clinically production facing genomic processing using cloud resources. Many of these projects have involved full stack development with collaboration and cooperation between multiple individuals, groups, and institutions. Along the way I have participated in research projects related to artificial intelligence, distributed systems, edge-computing, optimization, networking, and others.

After earning my Bachelor of Science in Computer Science in 2013 from the University of Kentucky I began working full time for the university in the Enterprise Architect Group where we researched and prototyped projects related to bayesian sentiment association, location-awareness through network access point tagging, distributed systems (control, optimizations, monitoring,) and cloud computation and storage infrastructure. One of my larger projects was using an edge-computing framework I helped develop to perform distributed genomic processing for clinical laboratories at UK Healthcare using our local private cloud infrastructure.

In 2015 I became a graduate student at the University of Kentucky with a focus on applications of artificial intelligence in health care and in 2017 I began working for UK Healthcare directly. While working at UK Healthcare I’ve upgraded our clinical genomic processing system to scale using public cloud infrastructure to reduce turn-around time and increase visibility into the processing workflow. Additionally, I’ve worked with our clinical pathologists on researching ways in which we can apply machine and deep learning systems to whole-slide imaging (WSI) in which gigapixel-scale images (100,000 x 100,000) are produced from tissue samples.