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.

Differences between men and women: role of stress, hostility and autonomic nervous system functions in health and cardiovascular disease; psychological distress and recurring syncopes; risk of hypertension/heart disease/heart attacks, pain sensitivity and clinical impact; psychological or psychophysiological interventions.

Methods used:

Experimental and/or prospective studies with psychosocial interviews, physiological monitoring and blood tests. Ecological validation of data with monitoring of day-to-day behaviour, emotions and/or symptoms.