Patricia Thaine keynote speaker

Patricia Thaine is a leading expert in artificial intelligence, data privacy, and privacy-preserving machine learning, and the Co-Founder and CEO of Limina, formerly Private AI. A researcher, entrepreneur, and technologist, Patricia is at the forefront of one of the most important challenges facing organizations today: how to unlock the value of AI and enterprise data without compromising privacy, security, or trust.

Patricia founded Private AI after recognizing a fundamental obstacle to the adoption of artificial intelligence: organizations possess enormous amounts of valuable data, but much of it contains sensitive, personal, or confidential information that cannot safely be used. Her company developed AI technology capable of identifying and protecting sensitive information across unstructured data, helping organizations use their data while meeting increasingly complex privacy and regulatory requirements.

In 2026, Private AI became Limina, reflecting a broader mission to help organizations cross the threshold between untapped data and realized value. The company focuses particularly on the challenge of unstructured enterprise data—the documents, conversations, images, audio, and other information that increasingly form the foundation of modern AI applications.

Patricia's expertise is grounded in more than a decade of research and software development. She is a Computer Science PhD candidate at the University of Toronto, currently on professional leave, where her research focuses on privacy-preserving natural language processing. Her academic work spans applied cryptography, de-identification, privacy-preserving machine learning, language technologies, and methods for protecting sensitive information while maintaining the usefulness of data.

Before founding her company, Patricia worked across research environments including the University of Toronto, McGill University, and the Public Health Agency of Canada. Her interdisciplinary background in computer science and linguistics gives her a distinctive perspective on the enormous quantities of sensitive information hidden inside human language and other forms of unstructured data.

Her work has received international recognition. Private AI was selected as a World Economic Forum Technology Pioneer and recognized as a Gartner Cool Vendor. Patricia is also the recipient of several academic awards and scholarships and is co-inventor of a U.S. patent related to secure word search.

As a speaker, Patricia brings together deep technical expertise and the practical experience of building an AI company around privacy and responsible data use. She helps audiences understand why AI strategy is increasingly inseparable from data strategy—and why organizations that cannot understand, govern, and safely use their data will struggle to capture the full potential of artificial intelligence.