Research Interests
My PhD research (on professional leave) is focused on privacy-preserving natural language processing.
Selected Academic Publications
Thaine, P., Penn, G. (2021). The Chinese Remainder Theorem for Compact, Task-Precise, Efficient and Secure Word Embeddings. In Proceedings of the 16th conference of the European Chapter of the Association for Computational Linguistics, EACL 2021.
Thaine, P., Penn, G. (2020). Vec2int: Applications of the Chinese Remainder Theorem in Word Embedding Compression and Arithmetic (Poster). Vector Institute Natural Language Processing Symposium, September 15 and 16, 2020.
Thaine, P., Penn, G. (2020). Reasoning about unstructured data de-identification. In Journal of Data Protection and Privacy, Vol. 3, No. 3.
Thaine, P., Penn, G. (2019). Vocalic and Consonantal Grapheme Classification through Spectral Decomposition. In Graphemics in the 21st Century, Proceedings of Grapholinguistics and Its Applications, Vol. 1.
Thaine, P., Penn, G. (2019). Extracting Bark-Frequency Cepstral Coefficients from Encrypted Signals. In Proceedings of INTERSPEECH, Graz, Austria. pdf blog
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. pdf
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. pdf
Thaine, P., Penn, G. (2018). Vocalic and Consonantal Grapheme Classification through Spectral Decomposition. In Graphemics in the 21st Century: Proceedings of the 2018 Conference (Grapholinguistics and Its Applications), Fluxus Editions. pdf amazon code
Thaine, P., Penn, G. (2017). Vowel and Consonant Classification through Spectral Decomposition. Proceedings of the First Workshop on Subword and Character Level Models in NLP, EMNLP, 2017. pdf code
Sultanum, N., Thaine, P., Brudno, M., Glueck, M., Wigdor, D., Chevalier, F. (2017, October). MedStory: Unlocking the Qualitative Power of Medical Narratives. In Proceedings of 8th Workshop on Visual Analytics in Healthcare (VAHC). pdf
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.
Patents
Thaine, P., Penn, G. (2022). Secure word search. US Patent 11,461,551.
Talks and Panels
Panel: AI in action: Real world adoption experiences from startups (February 22, 2024), MaRS Impact AI, Toronto, ON.
Navigating ChatGPT's Privacy Concerns: What You Need to Know (October 11, 2023), World Summit AI Amsterdam.
Panel: How to do more with AI (September 28, 2023), at Vamos Latam Summit by Latitud, Sao Paulo, Brazil.
Governing generative AI – Innovation vs. ownership (September 19, 2023), at DTW Ignite, Copenhagen, Denmark.
Panel:PERSPECTIVES AI and Film: Bridging the Gap Between Innovation and Responsibility (September 8, 2023), at Toronto International Film Festival (TIFF), Toronto, ON.
Addressing Privacy and the GDPR in ChatGPT and Large Language Models (September 6, 2023), at Voice & AI, Washington D.C.
Panel:Keynote Panel Future of Privacy (May 4, 2023), at Ecosystems 2030, A Coruna, Spain.
Demystifying Data Privacy and Regulatory Compliance for AI (April 19, 2023), at the World Summit AI Americas.
Responsible AI/Tech Startup Journey & Funding (June 8, 2022), at the Women in AI Ethics Mid-Year Summit 2022.
The Importance of Privacy in NLP (May 5, 2022), at the World Summit AI Americas, Montreal, Qc.
An Overview of Privacy-Preserving NLP (February 17, 2022), guest lecture at the University of Washington.
Dealing with Personal Data using AI (December 15, 2021), at the Better Ethics and Consumer Outcomes Network's Fireside Chat.
Privacy-Enhancing Technologies in AI Security (December 1, 2021), at O'Reilly Media's AI Superstream Series: Securing AI.
Panel: Big Data and Analytics Strategy at the Heart of Cybersecurity and Privacy (November 18, 2021), at Toronto Machine Learning Summit.
Panel: Demystifying the De-identification of Data (November 16, 2021), at The Innovation Game: Adopting RegTech in a Digital Age, Canadian Regulatory Technology Association.
Panel: Can voices be anonymised? (November 2, 2021), Lorentz Workshop on Speech as Personable Identifiable Information.
The Latest Advances in Privacy-Preserving NLP (September 21, 2021), Toronto Machine Leaning Summit on NLP.
Privacy Preserving Synthetic Data in AI/ML - A Mirage. (June 2, 2021), Privacy Symposium 2021 (Infosys - IAPP).
Efficient Evaluation of Activation Functions over Encrypted Data (January 15, 2021), UofT AI Conference.
Private-Preserving Machine Learning (December 3, 2020), MLOps: Production and Engineering Vancouver 2020.
Cybersecurity and Privacy: Complements for a more secure Internet (November 25, 2020), Keynote talk at Vector Institute Endless Summer School (ESS).
Panel moderator for The Role of ML in Climate Change (November 18, 2020), at Toronto Machine Learning Summit.
Privacy in Deployment (October 16, 2020), 2020 USENIX Conference on Privacy Engineering Practice and Respect (PEPR'20).
A Practical Guide to Privacy-Preserving Machine Learning (November 12, 2020), EVOKE CASCON 2020.
Privacy in Production (June 30, 2020), Canada AI/ML, Data Science and Engineering Digital Meetup.
Privacy-Preserving Machine Learning (June 18, 2020), MLOps: Production and Engineering World.
Privacy-Preserving Machine Learning: A Practical Overview (June 10, 2020), Vector Institute Endless Summer School (ESS).
An Overview of the Problem of Perfectly Privacy-Preserving AI (June 8, 2020), Future of Privacy Forum AI Working Group.
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
RegTech100, 2023.
Top CX Compliance Vendors, 2023.
Gartner® Cool Vendors™ in Privacy, 2023.
C100 Fellow (August 2023).
World Economic Forum Technology Pioneer (May 2023).
The Vector AI20 for 2023.
EY Women in Tech Award (October 2020).
Satchu Prize in recognition of outstanding performance in the program and a demonstrated potential to lead Canada's next generation of high impact entrepreneurs (October 2020).
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).
Service to the Community
Co-Organizer, PrivateNLP Workshop (July 2022), co-located with NAACL 2022.
Co-Organizer, PrivateNLP Workshop (June 2021), co-located with NAACL 2021.
Reviewer, Journal of Medical Internet Research (August 2020).
Program Committee Member, EMNLP 2020.
Co-Organizer, PrivateNLP Workshop (November 20 2020), co-located with EMNLP 2020.
Co-Organizer, PrivateNLP Workshop (February 7 2020), co-located with the 13th ACM International WSDM Conference (WSDM 2020).
Program Committee Member, 2019 Privacy-Enhancing Artificial Intelligence and Language Technologies AAAI Spring Symposium.
Program Committee Member in the area of Ethics, Bias, and Fairness, NAACL-HLT 2019.
Program Committee Member, Eighth Joint Conference on Lexical and Computational Semantics (SEM 2019).
Reviewer, Computational Linguistics Journal (November 2017, April 2017, July 2019).
Reviewer, Computational Intelligence Journal (March 2018).
Reviewer, Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15).
Media Coverage
Strategy + Business, A PWC Publication, From principles to practice: Responsible AI in action, commentary, February 20, 2024.
Forbes, NLP Evolution: Changes Coming To The Ways We Interact With Technology, commentary, February 15, 2024.
Microsoft News Centre Canada, Canada's AI Predictions for 2024, commentary, January, 2024.
The Shifting Privacy Left Podcast, S3E1: "Privacy-preserving Machine Learning and NLP" with Patricia Thaine (Private AI), podcast interview, January 2, 2024.
Technopedia, Decentralized Artificial Intelligence (DAI), commentary, December 5, 2023.
Forbes, 20 Best Practices For Using Data Center As A Service Facilities, commentary, November 9, 2023.
The Virtual CISO Podcast, An Introduction to AI and its Place in the Work Place with CEO of Private AI Patricia Thaine, podcast interview, October, 2023.
Techfinitive, Patricia Thaine, Private AI: “When building something, only jump on waves if it fits your vision”, interview, September 25, 2023.
CMSWire, Will Targeted Advertising Survive Privacy Legislation?, commentary, September 15, 2023.
Screen Daily, Actors need to negotiate now to protect against future AI developments - TIFF AI panel, article, September 8, 2023.
Experts in Technology by Syapse, Keeping AI privacy front and center to create better patient experiences, products, and standards (Part 2/2), podcast interview, September, 2023.
The FIT4PRIVACY Podcast, ChatGPT & Privacy Risks with Patricia Thaine and Punit Bhatia in The FIT4Privacy Podcast E094 S4, podcast interview, September, 2023.
Experts in Technology by Syapse, Understanding data privacy and its critical – but often overlooked – role in AI (Part 1/2), podcast interview, August, 2023.
Technopedia, LLMs in the Legal Field: Transforming Legal Research and Analysis, commentary, June 27, 2023.
Canada Venture, Unveiling the Top 15 Cyber Security Startups in Canada You Need to Know, article, June 27, 2023.
Financial Post, Private AI selected as 2023 Technology Pioneer by World Economic Forum, article, June 23, 2023.
IT Business, Private AI selected as 2023 Technology Pioneer by World Economic Forum, article, June 23, 2023.
IT World Canada, Private AI selected as 2023 Technology Pioneer by World Economic Forum, article, June 23, 2023.
Technology For You, World Economic Forum announces selection of 100 most promising Technology Pioneers, companies making progress in sustainability, advanced manufacturing and inclusive healthcare, article, June 21, 2023.
Safety Detectives, Interview with Patricia Thaine - Co-Founder at Private AI, interview, June, 2023.
Help Net Security, ChatGPT and data protection laws: Compliance challenges for businesses, interview, June 20, 2023.
Diginomica, Personal AI vs Private AI – we speak to the founder–CEOs of two contrasting start-ups, article, May 30, 2023.
ESG Explorer Podcast, The growth mindset – lessons learned from women founders, podcast interview, May 23, 2023.
The Fintech Times, What Are the Biggest Compliance Challenges and How Are They Overcome? Industry Responds, commentary, May 16, 2023.
Ecosystems 2030, Patricia Thaine - Privacy & AI - Interview at Ecosystems 2030 Ch3, interview, May 5, 2023.
IT World Canada, Private AI says its new offering allows firms to safely leverage ChatGPT, article, May 2, 2023.
Dark Reading, PrivateGPT Tackles Sensitive Info in ChatGPT Prompts, article, May 2, 2023.
Help Net Security, PrivateGPT enables users to share only necessary information with OpenAI’s chatbot, article, May 2, 2023.
Venturebeat, Private AI’s PrivateGPT aims to combat ChatGPT privacy concerns, article, May 1, 2023.
Category Visionaries, Patricia Thaine, Co-Founder & CEO of Private AI: Over $11 Million Raised to Help Organizations Anonymize PII to Achieve Regulatory Compliance, podcast interview, April, 2023.
Made in CA, Patricia Thaine: Private AI Enabling Companies To Protect Their Customers’ Information While Fully Utilizing Their Data, interview, 2023.
Vux World, The need for AI privacy, with Patricia Thaine, CEO, Private AI, podcast interview, May 19, 2022.
This Week In Voice, Women Leaders of Conversational AI, Class of 2023, announced, article, October 11, 2022.
CEO Weekly, Need to collect data? There are ways to make it safer, says Private AI, article, October 4, 2022.
Unstructured Unlocked, Unstructured Unlocked episode 5 with Patricia Thaine, podcast interview, September 28, 2022.
City News, Startups get the Opportunity to Make their Pitch at Collision Conference, article, June 21, 2022.
Microsoft Canada, Microsoft Expl(ai)n: "Can we trust AI?" with Patricia Thaine, Private AI, Microsoft Expl(ai)n Series, June 8, 2022.
Applied Privacy Podcast, In Conversation with Patricia Thaine - CEO and Co-Founder of Private AI, podcast interview, June 27, 2022.
Vux World, The need for AI privacy, with Patricia Thaine, CEO, Private AI, podcast interview, May 19, 2022.
Betakit, Five Canadian Startups Crack CB Insights' 2022 AI 100 List, article, May 18, 2022.
Communitech Tech News, AI's wild west: Panel discusses ethics and artificial intelligence, article, May 17, 2022.
Catalog & Cocktails, Your privacy is my currency with Patricia Thaine from Private AI, podcast interview, March 10, 2022.
Privacy Tech Talk, Privacy Tech Talk: Private AI, podcast interview, February 20, 2022.
Caveat, Developer Challenges in Preserving Privacy, podcast interview, February 10, 2022.
Total Security Advisor, Top Predictions for the Privacy Space in 2022, article, December 28, 2021.
Dark Reading, 5 Things ML Teams Should Know About Privacy and the GDPR, article, November 17, 2021.
The Last Watchdog and Security Boulevard, Guest Essay: How stricter data privacy laws have redefined the ‘filing’ of our personal data, guest essay, November 4th, 2021.
Unite.ai, An interview with Patricia Thaine, CEO at Private AI, interview, October 19, 2021.
TechTarget, FTC pursues AI regulation, bans biased algorithms, commentary, October 19, 2021.
Betanews, Industry leaders comment on Cybersecurity Awareness Month, commentary, October, 2021.
Security Magazine, October marks Cybersecurity Awareness Month: Security experts comment on where efforts should be focused, commentary, October 1, 2021.
insideBigData, Heard on the Street - 9/27/2021, commentary, September 27, 2021.
Press Release, Private AI secures $3.15M seed round to streamline privacy compliance for enterprises, announcement, September 15, 2021. Published in Fortune's Term Sheet Newsletter, BetaKit, Cyberwire, MarTech Series, AI Techpark, TMCNet, Private Capital Journal, Enterprise AI, AiThority, Dark Reading, Fintech Global, CX Today, Venture Capital Journal, insideBigData, and Analytics Insight.
Threat Technology, Private AI Delivers companies an easy-to-deploy way to redact sensitive data on the files they share, interview, September 9, 2021.
Invest Ontario, 10 cybersecurity companies to watch in 2021, article, August 6, 2021.
The Local Maximum, Episode 181 - Redacting your Secrets, podcast interview, July 19, 2021.
Threat Technology, These are the Top Cyber Security Companies in Toronto (2021), article, January 23, 2021.
Forbes, This Startup Founder Sees A Data Privacy Reckoning On The Horizon, interview, January 21, 2021.
Founded by Women, featured in book, January 7, 2021.
Privacy by Design Lab (Japan), Privacy Talk with Patricia Thaine, Co-Founder and CEO of Private AI, interview, January 2, 2021.
Datacast, Episode 42: Privacy-Preserving Natural Language Processing with Patricia Thaine, podcast, September 11, 2020.
Blog Posts
Thoughts on AI Regulation, November 2, 2023.
The Future of Software: Trust by Default and the Big Tech Pioneers Leading the Way, July 29, 2023.
Why The Right To Be Forgotten Is Even Harder To Comply With Than You Think (And What To Do About It), January 16, 2023.
Data Protection Regulations NLP Teams should Watch for in 2022, January 17, 2022.
Anonymized data is useless: fact or fiction?, August 17, 2021.
Data Anonymization: Perspectives from a Former Skeptic, June 4, 2021.
Demystifying De-identification: Understanding key tech for data protection regulation compliance, April 6, 2021.
Cybersecurity and Privacy: Complements for a more secure Internet, December 14, 2020.
Privacy Enhancing Technologies Decision Tree (v2), October 18, 2020.
Perfectly Privacy-Preserving AI: What is it and how do we achieve it?, January 1, 2020.
Homommorphic Encryption for Beginners: A Practical Guide (Part 2: The Fourier Transform), September 3, 2019.
Differentially Private Natural Language Processing, January 28, 2019.
Homomorphic Encryption for Beginners: A Practical Guide (Part 1), December 26, 2018.
Why is Privacy-Preserving Natural Language Processing Important?, June 26, 2018.
A Brief Overview of Privacy-Preserving Software Methods, May 22, 2018.
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