Patricia Thaine

Ph.D. Candidate under the supervision of Professor Gerald Penn
Computational Linguistics group
Department of Computer Science
University of Toronto
Bahen Centre for Information Technology
40 St. George Street, Room 4202C
pthaineATcs.toronto.edu Github LinkedIn

Research Interests
My PhD research is focused on privacy-preserving natural language processing.

Selected Publications
Thaine, P., Gorbunov, S., Penn, G. (2019). Efficient Evaluation of Activation Functions over Encrypted Data. In Proceedings of the 2nd Deep Learning and Security Workshop, 40th IEEE Symposium on Security and Privacy, San Francisco, USA.
Thaine, P., Penn, G. (2019). Perfectly Privacy-Preserving AI: What is it and how do we achieve it? (Poster). Canada-United Kingdom Symposium on Ethics in Artificial Intelligence, EIAI-2019, Ottawa, Canada.
Thaine, P., Penn, G. (2019). Privacy-Preserving Character Language Modelling. In Proceedings of the Privacy-Enhancing Artificial Intelligence and Language Technologies AAAI Spring Symposium, PAL 2019, Stanford University, Palo Alto, USA.
Thaine, P., Penn, G. (2018). Vowel and Consonant Classification through Spectral Decomposition. Proceedings of the First Workshop on Subword and Character Level Models in NLP, EMNLP, 2017. pdf code
Thaine P., Penn, G. (2016). A Survey of the State-of-the-Art in Acoustic Forensics. In Proceedings of the 18th Interpol Forensic Science Symposium, Lyon, France. 2016.
Rudzicz, F., Frydenlund, A., Robertson, S., Thaine, P. (2016, March). Acoustic-articulatory relationships and inversion in sum-product and deep-belief networks. In Speech Communication. pdf
Thaine, P., Penn, G. (2015, July). Writing Systems (Poster). Linguistic Society of America Linguistic Summer Institute, Chicago, IL.

Invited Talks
Upcoming (July 5, 2019): Privacy-Preserving Natural Language Processing Using Homomorphic Encryption (2019), National Research Council of Canada, Ottawa, CA.
Privacy-Preserving Natural Language Processing Using Homomorphic Encryption (2019), Borealis AI, Toronto, CA.
Perfectly Privacy-Preserving AI: What is it and how do we achieve it? (2019), Identity, Privacy, and Security Institute, Toronto.
Privacy-Preserving Natural Language Processing (2018), Vector Institute for Artificial Intelligence, Toronto, CA.
Vowel and Consonant Classification through Spectral Decomposition (2017), National Research Council of Canada, Ottawa, CA.

Awards
RBC Graduate Fellowship in recognition of excellence in research and interest in commercialization (2019 – 2021)
NSERC PGSD in recognition of excellence in research and academic performance (2017 – 2020)
Beatrice "Trixie" Worsley Graduate Scholarship in Computer Science (November, 2017)
Ontario Graduate Scholarship in recognition of excellence in research and academic performance (2016 – 2017)