Noah Marchal

I'm a data analyst at the University of Missouri 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 ambient intelligence. 

My PhD dissertation research area is in the use pervasive computing and AI for the healthcare domain, with particular focus on novel ad-hoc machine learning models of multi-modal sensor and electronic medical records as components for augmented decision support interfaces. The primary application of my research is for adaptive model building using continual machine learning and meta-modelling 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 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 family, studio and en plein air painting, LEGOs, distance running, cycling, board games, box puzzles, sudoko, catching Pokemon, and reading.