Noah Marchal

I'm a research analyst at the Biomedical Informatics, Biostatistics and Medical Epidemiology (BBME) Department in the School of Medicine at the University of Missouri.

My PhD dissertation topic was on the use of pervasive computing and AI in the healthcare domain, focusing on multi-modal machine learning of biophysical sensor monitoring and electronic health record data for tracking progressive functional decline in aging and neurodegenerative diease patients. The primary application of my research is to support clinicial decision making through the use of continual learning and decision ensembling to generate precision health analytics by targeting clinical assessment instruments with continous sensor measurement data. 

My long-term research interests are in responsive or natural computation: structures which incorporate real-world event phenomena and human-in-the-loop processes as a model for ambient intelligence (Aml). I have additional interests in the computational mediation 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, collecting LEGOs, distance running, cycling, board games, sudoko, and reading new journal articles.