Noah Marchal

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

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

My PhD dissertation research topic is on the use of pervasive computing and AI in the healthcare domain, focusing on novel machine learning models of multi-modal biophysical sensor and electronic medical records for addressing progressive functional decline in aging and chronic disease patients. The primary application is for adaptive modeling to support clinicial decision making through the use of continual, incremental learning and decision ensembling techniques to generate precision health analytics targeting clinical functional 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, sudoko, and reading papers.