My research activities focus on the cognitive aspects of visual processing, in both normal individuals and those who have suffered brain injuries. My main objectives are to identify the normal mechanisms involved in visual processing and to characterize the functional deficits resulting from brain damage. I use behavioural and electrophysiological methods. My current projects concern a number of themes:

1. Reading: visual mechanisms (i.e. shape perception and visuospatial attention) involved in accessing orthographic-lexical knowledge when recognizing written words, and organization of the lexical representation system
2. Visual recognition of objects: properties of the system for encoding visual shapes and representation of structural knowledge

Shahab's research is centered at the intersection of neuroscience and AI, also known as NeuroAI. Specifically, he examines visual perception and learning in both biological brains and artificial neural networks. He uses deep learning as a computational framework to model learning and perception in the brain, and leverages our understanding of the nervous system to create more biologically-inspired artificial intelligence.