Grant McKenzie
Title:
Associate Professor
Research areas:
Spatial Data Science
Geographic Information Science
Biography:
Grant McKenzie is an associate professor of spatial data science in the Department of Geography at McGill University. At McGill, Grant leads the Platial Analysis Lab, an interdisciplinary research group that works at the intersection of information science and behavioural geography. Much of Grant's work examines how human activity patterns vary within and between local regions and global communities. This has driven his applied interests geoprivacy and new mobility services as well as the broader role that geographic information science plays at the intersection of information technologies and society. Outside of academia, Grant has worked as a data scientist and software developer for a range of NGOs and leading technology companies.
Current research:
- Location privacy and trust
- Assessing the urban impacts of shared micromobility services
- Temporal dynamics in urban environments
Degree(s):
- PhD in Geography, UC Santa Barbara (2015)
- M. Applied Science, University of Melbourne (2008)
- BA Geography, University of British Columbia (2002)
Selected publications:
- McKenzie, G. , Romm, D., Féré, C., Balarezo, M.L.G. (2025) Gender differences in urban recreational running: A data-driven approach. Journal of Transport Geography. 124. 104171. Elsevier.
- Qiang, D., McKenzie, G. (2024) Navigating the Post-Pandemic Urban Landscape: Disparities in Transportation Recovery & Regional Insights from New York City. Computers, Environment and Urban Systems. Elsevier.
- Verma, P., McKenzie, G. (2024) Regional Comparison of Socio-Demographic Variation in Urban E-scooter Usage. Environment and Planning B: Urban Analytics and City Science (Special issue on Spatial Inequalities and Cities). Sage
- McKenzie, G., Zhang, H. (2023) Platial k-anonymity: Improving location anonymity through temporal popularity signatures. Proceedings of the 12th International Conference on Geographic Information Science. Schloss Dagstuhl-Leibniz-Zentrum für Informatik. (September 13-15; Leeds, UK)
- McKenzie, G., Romm, D., Zhang, H., Brunila, M. (2022) PrivyTo: A privacy preserving location sharing platform. Transactions in GIS. 26(4). pp. 1703-1717. Wiley Press.
Group:
Faculty