I'm a statistical programmer and data analyst at the University of Missouri Center to Stream Healthcare In-Place (C2SHIP) and a PhD student at the MU Institute for Data Science and Informatics.
I have long-term research interest in methods for what could be considered as responsive or natural computation: processes which incorporate real-world event phenomena with program logic structures for intelligence.
My PhD dissertation research area is in the use pervasive computing and AI for the healthcare domain, with particular focus on ad-hoc machine learning models of multi-modal sensor and electronic medical records systems as components for novel augmented decision support interfaces. The primary application of my research is for adaptive model building using meta-model and meta-information techniques to generate precision health analytics. I have additional interest in the computational mediation of human motor functioning and rehabilitation through remote analysis and verification for clinical therapy, and the impact of biotelemetry monitoring on quality of life for aging populations.
Adaptive model building with meta-information for generating precision analytics.
Data pipeline integrating sensor data and EMR with meta-information for CDSS models.
When not crunching numbers and chewing pencils, I enjoy spending quality time with my wife and sons, studio and en plein air painting, practicing my draftsmanship, being outdoors, collecting anthropomorphic LEGO sets, distance running, board games, box puzzles, catching Pokemon, and reading armchair non-fiction.
I listen to the Grateful Dead, Radiohead, Gregory Isaacs, Yo-Yo Ma, Big Something, Snoop Dogg, Little Dragon, Phish, Culture, Gorillaz, Medeski Martin and Wood, Erik Satie, 99.5 WCRB, 88.1 KDHX.