Erin Grant, PhD, BSc

Availability

📌 I am actively recruiting for my lab; see "Announcements" below.

About

I am 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).

Prior to joining the University of Alberta, I was an Assistant Professor / Faculty Fellow at the Center for Data Science at New York University, and before that, a Senior Research Fellow at the Gatsby Computational Neuroscience Unit and the Sainsbury Wellcome Centre at University College London. I earned my Ph.D. from the University of California, Berkeley in 2022 with support from the Natural Sciences and Engineering Research Council of Canada (NSERC). During my doctorate, I also worked as a research intern at OpenAI, Google Brain, and DeepMind.

I am passionate about giving back to my research communities. I currently serve on the Board of Directors of the nonprofit Women in Machine Learning, have been a member of the organizing committees of conferences in machine learning, cognitive science and neuroscience (ICLR, NeurIPS, CCN) and have regularly co-organized topical workshops within my research interests (Re-Align, Analytical Connectionism, Data on the Brain & Mind).

Research

My 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. My research combines modelling (simulations with and mathematical analysis of artificial neural networks and Bayesian methods) and experimental testing against neural and behavioural data from humans and other animals. Using these methods, I aim to identify how simple computational principles of learning and generalization enable complex abilities like vision, language, and planning, and to use these insights both to deepen our understanding of biological intelligence and to build more robust and transparent artificial intelligence.

See my publications for more details.

Teaching

I teach undergraduate and graduate courses across the Psychology and Computing Science departments. In Winter 2027 I am teaching CMPUT 267: Machine Learning I, a mathematically inclined introduction to the foundations of machine learning. My previous teaching includes graduate courses in machine learning and applied mathematics, most recently DS-GA 1018: Probabilistic Time Series Analysis Fall 2025 at New York University.

📌 I am actively seeking motivated trainees at all levels (research intern, undergraduate research student, Master's, PhD, postdoc) with strong backgrounds in computational methods, machine learning, cognitive science, or neuroscience to join my lab.

(🌻) To express interest in working with me, please fill out this enquiry form. I aim to respond to genuine enquiries submitted via this form within 4 weeks, with faster responses outside the September-to-December application season. (Master's and PhD applications also require submitting a standardized application by a specific deadline; see the Note below). There is no need to additionally email me once you have submitted this form, and doing so will not ensure a faster response.

Please do not reach out over email to enquire about working with me; use the enquiry form (🌻) instead. Due to the number of emails I receive on the topic, I am unlikely to respond to direct enquiries if we haven't had prior contact ("cold emails"). I am more likely to be able to respond to a submission to the form, as it asks for the information I need. If you would still like to email me for such an enquiry, please make sure to demonstrate genuine engagement with my research (e.g., by reading a few of my papers so that you can outline how your research interests align with the directions of my lab). Generic and AI-generated enquiries that do not (or only superficially) engage with my research make a negative impression, and I will not respond to them.

Note on Master's / PhD applications:

I will review applications to graduate degree (Master's, PhD) programs at the University of Alberta in the application cycle each Fall. I can supervise Master's and PhD students through Psychology (deadline December 1st), Computing Science (deadline December 15th), or the Neuroscience and Mental Health Institute (NMHI; deadline around May 1st). (Please note that in Canada, students typically complete a Master's degree before beginning their PhD, so if you do not already have a Master’s degree, please apply to the relevant Master's program.) If you are interested in working with me, please apply to one of these programs, and mention my name in your application. To make sure I see your application, please also fill out the form at (🌻).

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