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.

Karim Jerbi heads the Computational and Cognitive Neuroscience Lab (CoCo Lab) at UdeM. His research lies at the cross-roads between computational, systems and cognitive neuroscience, with an emphasis on exploring biological and artificial network dynamics. The research he leads seeks to elucidate the role of large-scale brain network dynamics in normal cognitive processes and their breakdown in psychiatric disorders. To this end, his research relies on a combination of invasive (intracranial electroencephalography, iEEG) and non-invasive (EEG and MEG) recordings, combined with advanced signal processing and artificial intelligence tools, including machine learning.

Karim Jerbi is interested in inter-disciplinary research questions such as the neural basis of attention, decision-making, states of consciousness and sleep, and has a keen interest in various forms of interaction between art, creativity and neuroscience.