Michael recently joined ActiGraph as a senior data scientist after working at Biofourmis for the previous five years. His work has leveraged data analytics and machine learning techniques to understand how various types of data from digital health technologies can be used to monitor for, detect, or predict adverse patient events or outcomes. This work has consistently focused on designing practical systems that make use of data available in existing workflows and have valuable intended uses.
Prior to joining Biofourmis, Michael received his PhD from Georgia Tech in 2020. His thesis fell at the intersection of human-robot interaction and human-human relationship modeling. He examined how robots could identify and help to deescalate destructive conflict in hierarchical human relationships.
