Noah Marchal

I'm a data analyst at the University of Missouri School of Medicine and a PhD student at the MU Institute for Data Science and Informatics.

I have long-term research interest in responsive or natural computation for ambient intelligence: processes which incorporate real-world event phenomena with program logic structures. 

My PhD dissertation research area is in the use pervasive computing and AI in the healthcare domain, focusing on novel predictive machine learning models of multi-modal biophysical sensor and electronic medical records to support clinicial decision making. The primary application is for adaptive modeling, using continual machine learning and meta-ensembling techniques to generate precision health analytics, of older adults and progressive disease patient populations targeting clinical functional measuremeng instruments with remote sensor data. I have additional interest in computational methods for the analysis of human motor function and impact of biotelemetry monitoring on quality of life. 

When not crunching numbers and chewing pencils, I enjoy spending quality time with my family, studio and en plein air landscape painting, LEGOs, distance running, cycling, board games, box puzzles, sudoko, catching Pokemon, and reading papers.