In collaboration with the Waisman Laboratory for Brain Imaging and Behavior, Moo works on the development of various brain image and network analysis tools for collaborators who wish to test specific biological hypotheses related to well-being.
Moo’s main research area is computational neuroanatomy, where noninvasive brain imaging modalities such as magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) are used to map the spatiotemporal dynamics of the human brain. His research concentrates on the methodological development required for quantifying and contrasting anatomical shape variations in both normal and clinical populations at the macroscopic level using various mathematical, statistical and computational techniques.
Moo received his Ph.D. in Statistics from McGill University under Keith J. Worsley and James O. Ramsay in 2001.
Education
Ph.D., Statistics, McGill University
M.Sc., University of Toronto
B.Sc., McGill University