University-industry research partnerships

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University of Toronto | Artificial Intelligence

Key facilities

Vector Institute for Artificial Intelligence is focused on building and sustaining AI-based innovation, growth and productivity in Canada by using the transformative potential of deep learning and machine learning.

Institute for Robotics and Mechatronics is a central hub for collaborative, multidisciplinary robotics and mechatronics research projects and innovative educational programs.

Creative Destruction Lab (CDL): CDL’s AI Stream brings together many of the world’s AI pioneers, including researchers, entrepreneurs, angel investors and venture capitalists at the forefront of investment in AI. CDL startups work with these mentors to sharpen objectives, prioritize time and resources, raise capital from visionary investors, and engage with the frontiers of research.

Major collaborations

Machine Learning for Health (ML4H) seeks to applying machine learning to understand and improve health. Researchers are developing a variety of ML tools, including ones designed to predict immediate and long-term patient needs to inform decisions in intensive care and ambulatory care units.

Deep Learning and Bayesian Modeling aims to develop architectures and algorithms that train faster, generalize better, give calibrated uncertainty, and uncover the structure underlying a problem, including the important and neglected problem of ensuring that AI systems remain aligned with human values.

NSERC Strategic Partnership Network in Computer Hardware for Emerging Sensory Applications (COHESA) brings together researchers from academia and industry to develop hardware that can deliver faster speeds and better performance for machine learning applications, from image recognition to autonomous vehicles. The project aims to create the next generation of computing engines optimized for artificial intelligence.


Brian Cantwell-Smith, Reid Hoffman Chair in AI and the Human – Research focuses on nature of AI and its impact on humanity.

David Duvenaud, Canada Research Chair in Generative Modelling – Research focuses on approximate inference, automatic model-building, model-based optimization.

Brendan Frey, Canada Research Chair in Information Processing and Machine Learning – Research focuses on deep learning techniques, to advance biology, medicine and healthcare.

Anna Goldenberg, Canada Research Chair in Computational Medicine – Research focuses on machine learning methods that can help understand the various factors that cause a particular disease.

Roger Grosse, Canada Research Chair in Probabilistic Inference and Deep Learning – Research focuses on algorithms for deep learning and Bayesian learning.

Aleksandar Nikolov, Canada Research Chair in Algorithms and Private Data Analysis – Research focuses on discrepancy theory and theoretical foundations of private data analysis (differential privacy).

Special programs and work integrated learning initiatives

Engineering Science Major in Machine Intelligence
Program focuses on development and application of algorithms that can learn and make decisions based on data, with the goal of producing graduates who can build mathematical models and create computer architectures optimized for AI applications.

Master of Science in Applied Computing: This program prepares students for lifelong success as technical leaders in information technology, and includes an eight-month internship at an information technology company during which students apply research results to real-world problems.


  • General Electric
  • IBM Canada
  • LG
  • LinkedIn
  • Royal Bank of Canada
  • Samsung
  • Toyota Motor Corporation
  • Uber

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