Main research area: Vision
Born in the rural southwest and raised in different cities, Julie is an American who has grown up traversing across the United States. Having always held a fascination for the brain-behaviour relationship, she began her education in psychology and cognitive science. During her master’s education, she developed an interest in computer modeling work, focusing on neural network modeling of visual processing and perception. In 2014, she accepted a DPhil position in computational neuroscience at The University of Oxford. Julie is also deeply interested in the impact of technology on policy, and has pursued policy work as well.
She has paused her studies to engage in fieldwork in the United States, and hopes to incorporate this experience into her future work. Artificial intelligence has given Julie an enthusiasm for using technology to solve real-world problems, as well as an incredible appreciation for the human mind and spirit.
Julie has focused her interests in the area of computational neuroscience, specifically the neural network modeling of primate vision, invariant object recognition, and colour perception. More recently, she is interested in using biologically realistic ‘spiking’ neural networks to better understand the binding problem, which concerns how the brain integrates sensory information to produce a unified and coherent percept of its world.