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Elizabeth Zavitz is an interdisciplinary computational neuroscientist at Monash University, focusing on biologically inspired algorithms for visual perception. Her research combines computational modeling, physiological recordings, and behavioral analysis to study how the brain encodes and transforms sensory information. She investigates how distributed neural populations represent complex visual patterns and textures in natural images, contributing to perceptual and behavioral outcomes. Elizabeth completed her Bachelor's Degree in Computing from Queen's University in 2007 and her PhD in Experimental Psychology from McGill University in 2013, followed by postdoctoral research in neural information processing in Australia. Her leadership promotes cross-disciplinary collaboration, integrating computational and empirical approaches to enhance understanding of visual coding in the brain and inform the development of medical technologies for artificial vision systems. Current research projects include examining how contextual experiences modulate neural responses, and using artificial neural networks to understand cortical representations and the influence of context on perception.
Monash University • Melbourne, Australia
Senior Lecturer in Electrical and Computer Systems Engineering with a focus on computational neuroscience and visual perception.
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