Nathan Odic is a Machine Learning Resident on the Advanced Technology team. He is currently working with ZeroKey to monitor industrial manufacturing operations that involve human workers. His project applies machine learning to computer vision and time series analysis to improve the efficiency of human-centered manufacturing processes.

Previously, Nathan was a research assistant at the National Research Council Canada, where he worked on high-precision autonomous welding robots. Nathan earned an MSc in Computing Science from Polytechnique Montréal, where his research focused on applying computer vision to industrial safety in human-robot collaboration. He also holds a French engineering degree from the École des Mines d’Alès.
Outside of work, Nathan enjoys going out with friends and watching basketball and soccer (especially Stade Rennais) on TV.