Seeking applications for fully funded Master’s degree

March 25, 2022

The Platial Analysis Lab is currently seeking students interested in completing a Master’s degree in Geography at McGill University starting Fall 2022. There is still time to apply! The positions are fully funded meaning that the lab will provide a stipend to cover living expenses in Montreal as well as any research-related costs.

Preference will be given to Quebec residents and those proficient in both French and English.

Topic: This project will involve working along side local communities and marine researchers to investigate marine vessel traffic, and more specifically, the waves generated by boats in the St. Lawrence River. As part of your Master’s degree you will develop and administer surveys, engage with local community groups, and conduct geospatial and statistical analysis.

If this sounds interesting and/or you would like to discuss further, please contact Professor Grant McKenzie at grant.mckenzie@mcgill.ca as soon as possible (before April 8, 2022).

More information on the McGill graduate program is available at:
• https://www.mcgill.ca/geography/graduate
• https://www.mcgill.ca/gps/

Know someone that might be interested? Share the Call through one of the links below.

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Le Platial Analysis Lab est à la recherche d’étudiant.e.s intéressé.e.s à compléter une maîtrise en géographie à l’Université McGill à partir de l’automne 2022. Il est encore temps de postuler ! Les postes sont entièrement financés, ce qui signifie que le laboratoire fournira une allocation pour couvrir les frais de subsistance à Montréal ainsi que tous les frais liés à la recherche.

Une préférence sera accordée aux candidat.e.s resident.e.s du Québec et à ceux/celles qui maîtrisent le français et l’anglais.

Sujet : Ce projet impliquera de travailler aux côtés des communautés locales et des chercheurs marins pour enquêter sur le trafic maritime des navires, et plus particulièrement sur les vagues générées par les bateaux dans le fleuve Saint-Laurent. Dans le cadre de votre maîtrise, vous développerez et administrerez des enquêtes, dialoguerez avec des groupes communautaires locaux et effectuerez des analyses géospatiales et statistiques.

Si cette offre vous intéresse et/ou si vous souhaitSi cette offre vous intéresse et/ou si vous souhaitez en discuter davantage, veuillez contacter le professeur Grant McKenzie à grant.mckenzie@mcgill.ca dès que possible (avant le 8 avril 2022).

Plus d’informations sur le programme d’études supérieures de McGill sont disponibles à:
• https://www.mcgill.ca/geography/graduate
• https://www.mcgill.ca/gps/

Vous connaissez quelqu’un qui pourrait être intéressé ? Merci de partager.

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Qiang, Dan; McKenzie, Grant

Navigating the Post-Pandemic Urban Landscape: Disparities in Transportation Recovery & Regional Insights from New York City Journal Article

In: Computers, Environment and Urban Systems, vol. 110, pp. 102111, 2024.

Abstract | Links | BibTeX

Verma, Priyanka; McKenzie, Grant

Regional Comparison of Socio-Demographic Variation in Urban E-scooter Usage Journal Article

In: Environment and Planning B: Urban Analytics and City Science, 2024.

Abstract | Links | BibTeX

@article{Verma2024,

title = {Regional Comparison of Socio-Demographic Variation in Urban E-scooter Usage},

author = {Priyanka Verma and Grant McKenzie},

url = {https://grantmckenzie.com/academics/Verma_2024.pdf},

year  = {2024},

date = {2024-03-26},

urldate = {2024-03-09},

journal = {Environment and Planning B: Urban Analytics and City Science},

abstract = {In recent years we have witnessed explosive growth in the shared, free-floating, electric scooter industry. While still controversial in many North American cities, a number of large e-scooter operators have managed to carve out a piece of the urban transportation landscape. As these vehicles shift from novelty services to increasingly reliable modes of short personal travel, the discussion has turned to investigating who exactly benefits from these micromobility services and who are being left behind. Though population surveys have been administered to identify the socio-demographic characteristics of e-scooter riders in the past, little work has linked these characteristics through trips, or investigated the regional variation in these demographic factors. In this work we explore the variability and similarities in e-scooter rider characteristics across three major U.S. cities. To accomplish this, we apply a Moran’s Eigenvector Spatial Filtering linear regression model and compare our results to more commonly used spatial regression approaches. Our results indicate that the spatial filtering approach outperforms other methods in identifying socio-demographic characteristics of e-scooter users, across multiple regions. We find that many socio-demographics associated with e-scooter usage are regionally variant, despite younger users making up the core user base in all cities. There are variations in usage based on gender, income, and race across cities with Black and Hispanic populations remaining underserved. The implications of these findings are discussed.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

Brunila, Mikael; LaViolette, Jack; CH-Wang, Sky; Verma, Priyanka; Féré, Clara; McKenzie, Grant

Toward a Critical Toponymy Framework for Named Entity Recognition: A Case Study of Airbnb in New York City Best Paper Proceedings Article

In: Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP2023), 2023.

Abstract | Links | BibTeX

McKenzie, Grant; Zhang, Hongyu

Platial k-anonymity: Improving location anonymity through temporal popularity signatures Best Paper Proceedings Article

In: Proceedings of the 12th International Conference on Geographic Information Science, Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik, 2023, ISSN: 1868-8969.

Abstract | Links | BibTeX

@inproceedings{McKenzie2023b,

title = {Platial k-anonymity: Improving location anonymity through temporal popularity signatures},

author = {Grant McKenzie and Hongyu Zhang },

url = {https://drops.dagstuhl.de/opus/volltexte/2023/18904/},

issn = {1868-8969},

year  = {2023},

date = {2023-08-31},

urldate = {2023-08-31},

booktitle = {Proceedings of the 12th International Conference on Geographic Information Science},

volume = {277},

publisher = {Schloss Dagstuhl -- Leibniz-Zentrum fur Informatik},

series = {Leibniz International Proceedings in Informatics (LIPIcs)},

abstract = {While it is increasingly necessary in today's digital society, sharing personal location information comes at a cost.  Sharing one's precise place of interest, e.g., Compass Coffee, enables a range of location-based services, but substantially reduces the individual's privacy.  Methods have been developed to obfuscate and anonymize location data while still maintaining a degree of utility.  One such approach, spatial k-anonymity, aims to ensure an individual's level of anonymity by reporting their location as a set of k potential locations rather than their actual location alone.  Larger values of k increase spatial anonymity while decreasing the utility of the location information.  Typical examples of spatial k-anonymized datasets present elements as simple geographic points with no attributes or contextual information.  In this work, we demonstrate that the addition of publicly available contextual data can significantly reduce the anonymity of a k-anonymized dataset.  Through the analysis of place type temporal visitation patterns, hours of operation, and popularity values, one's anonymity can decreased by more than 50 percent.  We propose a platial k-anonymity approach that leverages a combination of temporal popularity signatures and report the amount that k must increase in order to maintain a certain level of anonymity. Finally, a method for reporting platial k-anonymous regions is presented and the implications of our methods are discussed.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}