Noah Marchal

I'm a research 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: structures which incorporate real-world event phenomena and human-in-the-loop processes as a model for ambient intelligence. 

My PhD dissertation research topic is on the use of pervasive computing and AI in the healthcare domain, focusing on novel machine learning of multi-modal biophysical sensor and electronic health record data for addressing 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. I have additional interests in the computational mediation of human motor function and impact of biotelemetry monitoring on quality of life in vulnerable and at-risk populations. 

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 new research papers.