Skip to content
CIFAR header logo
fr
menu_mobile_logo_alt
  • Our Impact
    • Why CIFAR?
    • Impact Clusters
    • News
    • CIFAR Strategy
    • Nurturing a Resilient Earth
    • AI Impact
    • Donor Impact
    • CIFAR 40
  • Events
  • Programs
    • Research Programs
    • Pan-Canadian AI Strategy
    • Next Generation Initiatives
    • CIFAR Arrell Future of Food Initiative
  • People
    • Fellows & Advisors
    • CIFAR Global Scholars
    • Canada CIFAR AI Chairs
    • AI Strategy Leadership
    • Leadership
    • Staff Directory
  • Support Us
  • About
    • Our Story
    • Awards
    • Partnerships
    • Publications & Reports
    • Careers
    • Equity, Diversity & Inclusion
    • Statement on Institutional Neutrality
    • Research Security
  • fr
  • Home
  • Bio

Follow Us

GS_Erin Grant

Erin Grant

Appointment

Canada CIFAR AI Chair

CIFAR Global Scholars 2026-2028

Learning in Machines & Brains

Pan-Canadian AI Strategy

Connect

Webpage

About

Erin Grant is an Assistant Professor jointly appointed in the Departments of Psychology and Computing Science at the University of Alberta, and a Fellow at the Alberta Machine Intelligence Institute (Amii). Grant’s research bridges cognitive science, neuroscience and artificial intelligence to understand how biological and artificial intelligence systems build internal representations of the world that support perception, cognition and action. Learning and generalization are among the defining capacities of intelligent systems, shared across humans, other animals and machines. Grant aims to identify how these simple computational principles enable complex abilities like vision, language, decision-making and planning, and to apply these insights to advance both our understanding of biological intelligence and the development of more robust and transparent artificial intelligence systems.

Awards

  • Rising Star of Neuroscience, The Transmitter, 2025
  • Postgraduate Scholarship, Doctoral, NSERC, 2020

Relevant Publications

  • Braun, L., Grant, E., & Saxe, A. M. (2025). Not all solutions are created equal: An analytical dissociation of functional and representational similarity in deep linear neural networks. Proceedings of 42nd International Conference on Machine Learning.
  • Lufkin, L., Saxe, A., & Grant, E. (2024). Nonlinear dynamics of localization in neural receptive fields. Advances in Neural Information Processing Systems, 37, 25938–25960.
  • Grant, E., Finn, C., Levine, S., Darrell, T., & Griffiths, T. (2018). Recasting gradient-based meta-learning as hierarchical bayes. Proceedings of the 6th International Conference on Learning Representations.

Institution

Amii

University of Alberta

Department

Departments of Psychology & Computing Science

Education

  • PhD (Computer Science), University of California, Berkeley
  • BSc (Computer Science), University of Toronto

Country

Canada

Support Us

The Canadian Institute for Advanced Research (CIFAR) is a globally influential research organization proudly based in Canada. We mobilize the world’s most brilliant people across disciplines and at all career stages to advance transformative knowledge and solve humanity’s biggest problems, together. We are supported by the governments of Canada, Alberta and Québec, as well as Canadian and international foundations, individuals, corporations and partner organizations.

Donate Now
CIFAR header logo

MaRS Centre, West Tower
661 University Ave., Suite 505
Toronto, ON M5G 1M1 Canada

Contact Us
Media
Careers
Accessibility Policies
Supporters
Financial Reports
Subscribe

  • © Copyright 2026 CIFAR. All Rights Reserved.
  • Charitable Registration Number: 11921 9251 RR0001
  • Terms of Use
  • Privacy
  • Sitemap

Subscribe

Stay up to date on news & ideas from CIFAR.

This website stores cookies on your computer. These cookies are used to collect information about how you interact with our website and allow us to remember you. We use this information in order to improve and customize your browsing experience and for analytics and metrics about our visitors both on this website and other media. To find out more about the cookies we use, see our Privacy Policy.
Accept Learn more