The Platial Analysis Lab is a research group based out of McGill University at the intersection of geoinformatics and quantitative behavioral geography…

As the name suggests, the Lab pulls apart the concept of place, taking a data-driven and behavioral approach to understanding the dimensions of our world.

E-scooters in Canada

It has been a whirl-wind few weeks for shared mobility, and specifically Lime scooters, in Canada. Professor Grant McKenzie was asked to provide some insight into the future of e-scooters in Canada…

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Jump e-Bikes in Montreal

Last night, approximately 200 vehicles from Uber’s electric-assist bicycle-sharing service Jump, appeared on the streets of Montreal…

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Presentation to the MTL Machine Learning Group

Last week Grant McKenzie presented a talk entitled “A machine learning approach to identifying urban neighborhood names” at the Montreal Machine Learning Group meetup in downtown Montreal. Check out the video below.

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Projects

Micro-mobility Services

We are in the midst of a technology-induced paradigm shift in transportation.

Predicting Financial Access

Access to digital financial services is fundamental to enabling those living in poverty around the world to become more economically stable, prosperous, and resilient.

Urban Pulse

Visualization the Pulse of the City

Scientometrics

Data Enrichment, Knowledge Discovery and Interactive Visualization Tools

Neighborhood Delineation

Identification and delineation of neighborhoods based on user-contributed geospatial content

FrankenPlace

An interactive thematic map search engine

Lab Members

Grant McKenzie

Assistant Professor

Grant McKenzie is an assistant professor in the Department of Geography at McGill University in Montréal, Canada where he leads the Platial Analysis Lab, an interdisciplinary research group that works at the intersection of data science and behavioural geography. Much of Dr. McKenzie’s work examines how human activities vary within and between local neighbourhoods and global communities. This has driven his applied interests in financial accessibility, geoprivacy, and micro-mobility services as well as the broader role that spatial data science plays at the intersection of information technologies and society.  Dr. McKenzie is a founding member of the Seattle-based start-up consultancy Spatial Development International and has worked as a data scientist and software developer for a range of NGOs and leading technology companies.

Mikael Brunila

Doctoral Student

Mikael Brunila is a PhD student in Geography at McGill University. He graduated in 2017 as a Fulbright scholar from the Quantitative Methods in the Social Sciences program at Columbia University. He completed his Bachelor’s degree in Political Science with minor subjects in Economics and Computer Science at the University of Helsinki in 2016. Brunila uses GIS, Bayesian inference and natural language processing to study semantic geographies in the sharing economy, governance through data science and machine learning as well as urban social movements. He previously worked as a journalist and has co-authored books on the far-right in Finland, on the implementation of zero tolerance politics against graffiti in Helsinki and on the political economy of the Internet. Brunila is also a member of the Urban Politics and Governance Lab lead by professor David Wachsmuth.

Morgan Guttman

Research Assistant

Morgan is a 4th year student at McGill, completing a major in archaeology/anthropology and a minor in GIS and remote sensing. He is interested in the ways that these fields can compliment each other, especially the application of geographical perspectives in understanding the spatial variability of human cultural activities on the landscape, both in the past and the present. He continuously aims to learn more about GIS and quantitative methods for spatial analysis and has currently been accepted for the arts undergraduate research internship awards. He is working on a project over the summer analyzing place-based activity patterns in Montreal and Toronto, and he hopes to gain valuable experience in geospatial and statistical analysis from this internship.