Our renowned research community is advancing breakthroughs in the science and application of AI. From using quantum computing to address climate change, to developing new machine learning models for 3D applications, harnessing AI to improve food price forecasting, and more, Vector researchers are unlocking new ways to apply AI to drive better economic, health, and societal outcomes.

Our strategic research priorities

  • Machine Learning
  • Deep Learning
  • AI for Science
  • Trustworthy AI
  • AI for Health
  • Foundation Models

Vector is advancing its goal of becoming a top 10 global centre for AI research by attracting the world’s most accomplished, ambitious, and innovative researchers who are unlocking new achievements across a wide range of AI and machine learning topics.

714 Members of the Vector research community, comprising:

41
Faculty Members
38
Canada CIFAR AI Chairs
103
Faculty Affiliates
51
Postdoctoral Fellows
410
Graduate Researchers
115
Undergraduates

Our growing research team

What was once only a few founding faculty has evolved over the last five years into a flourishing community comprising over 700 researchers who are pushing the boundaries of AI, machine learning, and deep learning in critical areas to benefit Ontarians, Canadians, and people around the world.

Meet the Research Team

We drive this growth through new and expanding efforts to attract and develop an outstanding community

  • Fostering collaboration between industry and academia to connect leading research and AI applications.
  • Creating more ways for researchers to work with industry sponsors and health sector partners on real-world problems and novel data sets.
  • Expanding access to events focused on research and applications and increasing access to internships.
Vered Shwartz presenting

Published research

In dozens of timely, globally relevant, and impactful projects and work themes, these researchers are unlocking new ways to apply AI to drive better economic, health, and societal outcomes.

Browse Publications

Latest research news

Vector Institute Computer Vision Workshop showcases the field’s current capabilities and future potential

Vector Faculty Member Gautam Kamath

Vector researcher Gautam Kamath breaks down the latest developments in robustness and privacy

Standardized protocols are key to the responsible deployment of language models

The known unknowns: Vector researcher Geoff Pleiss digs deep into uncertainty to make ML models more accurate

Three people stare at a laptop with a Vector logo on it

Benchmarking xAI’s Grok-1

Vector Faculty Member Frank Rudzicz welcoming participants to the workshop.

Breaking Ground: Natural language processing headlines Vector Institute’s latest workshop gathering

Health Research

Improving health outcomes for everyone

Vector helps improve population health outcomes by creating an AI ecosystem that fosters innovation, enables better data collection and analysis, addresses staffing challenges, reduces wait times, and improves patient lives and care.

More about Health Research

Watch past Vector Distinguished Lectures Series talks

Introducing the Vector Distinguished Lecture Series by the Vector Institute—a public talk series for academic and industrial data scientists in the GTA to discuss advanced machine learning topics. This series will resume in September 2024.

Promise and Pitfalls of Public Data in Private ML
Gautam Kamath, Vector Faculty Member

Troubling Trajectories for Uncertainty Quantification and Decision Making with Neural Networks
Geoff Pleiss, Vector Faculty Member

Build an Ecosystem, Not a Monolith
Colin Raffel, Vector Faculty Member

Graph Neural Networks meet Spectral Graph Theory: A Case Study
Renjie Liao, Vector Faculty Member

Random matrix theory for high dimensional optimization, and an application to scaling laws
Elliot Paquette, Associate Professor at McGill University

AI Accelerating Scientific Understanding: Neural Operators for Learning on Function Spaces
Anima Anandkumar, Bren professor at Caltech

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