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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About Me
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Posts
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portfolio
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portfolioAcademic
Sentiment Keyboard
Detection and prevention of cyberbullying through the development of a client-based keyboard application which detects message sentiment via NLP and machine learning techniques. The keyboard application was built in Android Studio, with embedded NLP and machine learning techniques extracted from WEKA libraries. Built for a Summer project alongside Jacob Reckhard and Ibrahim Elmallah as part of the Ross and Verna Tate High School Internship Program. See details and press release for more information.
portfolioPersonal
CantoTools
A suite of tools to help language learners learn Cantonese. This is one of my favorite languages and has almost no resources publicly available. On top of this, year after year it is becoming an increasingly endangered language. Included is CantoRead, a standalone reader for written Cantonese. Includes Jyutping, frequency information and definitions extracted from the Words.hk online dictionary (included with build). Also includes persistent bookmark and known word storage. Future builds will focus on text analysis (like in Chinese Text Analyzer), improved dictionary coverage, pre-downloaded learning resources and beautification (still very basic). Also as part of CantoTools is YTCantoParse, a Colab-powered interactive application to scrape Cantonese youtube videos from an offline spreadsheet and present word frequency analysis. Can integrate with Migaku word dictionary information. Link to the repo: CantoTools
publications
Assessing the Capability of Deep-Learning Models in Parkinson’s Disease Diagnosis
C. West, S. Soltaninejad, and I. Cheng, “Assessing the Capability of Deep-Learning Models in Parkinson’s Disease Diagnosis,” in Lecture Notes in Computer Science, Springer International Publishing, 2020, pp. 237–247. doi: 10.1007/978-3-030-54407-2_20.
Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary
JF Rajotte, S Mukherjee, C Robinson, A Ortiz, C West, JL Ferres, RT Ng, “Reducing bias and increasing utility by federated generative modeling of medical images using a centralized adversary,” presented at the GoodIT ’21: Conference on Information Technology for Social Good, Sep. 2021. doi: 10.1145/3462203.3475875.
(note: see press release here)
[Preprint] Random (Un)rounding : Vulnerabilities in Discrete Attribute Disclosure in the 2021 Canadian Census
C. West, I. Vecna, R. Chowdhury, “Random (Un)rounding : Vulnerabilities in Discrete Attribute Disclosure in the 2021 Canadian Census,” currently in preprint, brought to the attention of the Canadian Census Bureau to highlight possible privacy issues with their latest Census disclosure