Research Engineer · PhD, University of Melbourne
I study how machines form concepts that generalise. My work brings machine learning into dialogue with cognitive science and philosophy of mind, asking what makes intelligent systems coherent, robust, and worthy of trust.
My doctoral thesis and peer-reviewed work on visual reasoning, abstraction, and generalisation.
The University of Melbourne
Perceptual abstraction and analogical reasoning in vision systems, examining what progressive matrix problems can tell us about generalisation and the organisation of concepts.
CVPR 2023
A visual reasoning challenge exploring how analogical relationships depend on context and interpretation, beyond a fixed inventory of objects and attributes.
ECCV 2020
An investigation of generalisation in abstract visual reasoning, using RAVEN to examine the relationship between task design and learned representations.
