I am in my second year at UBC’s Allard School of Law (class of 2021). I want use law to help give the weakest of us a voice, in the legal system and in society in general. This includes civil liberties, human rights, and democratic rights. I want to help with public legal education and access-to-justice initiatives, to give more of us more confidence in the outcomes of the legal system and other government decision-making processes. I’m also interested in the many overlaps of law and technology.
I am on the Gale Moot team and am the Associate Editor at the Canadian Journal of Family Law.
I’m trained as a computer scientist. In that field, I’ve focused on visual object recognition, machine learning, and applications of deep neural networks.
Formerly: data scientist at Kobo, head of R&D at Shelfie, communications-and-development volunteer at the BC Civil Liberties Association, flight instructor, Canadian Forces officer (Cadet Instructor Cadre), 2× Google intern (Maps, Research/YouTube).
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Here’s where you can find me elsewhere online:
Sancho McCann, “Finding Harmony: Law Society of British Columbia v Trinity Western University”, Case Comment, (2019) 28 Dalhousie Journal of Legal Studies 95.
Sancho McCann, Object classification and localization using spatially-localized features (PhD Dissertation, University of British Columbia, 2014) [unpublished].
Sancho McCann & David G Lowe, “Spatially-local coding for object recognition” in 11th Asian Conference on Computer Vision (Springer, 2012) 204.
Sancho McCann & David G Lowe, “Local naive Bayes nearest neighbor for image classification” in Computer Vision and Pattern Recognition (IEEE, 2012) 3650.
Sancho McCann, “Atmospheric Sounding Visualization” (course report, Information Visualization, Department of Computer Science, University of British Columbia, 2006) [unpublished].
A more complete list is at my Google Scholar profile.