Her research is cross-disciplinary, spanning human perception/cognition, computer vision, and cognitive neuroscience, focusing on research questions at the intersection of the three domains. Her work in Computational Perception and Cognition builds on the synergy between human and machine perception and cognition, and how it applies to solving high-level recognition problems like understanding scenes and events, perceiving space, localizing sounds, recognizing objects, modelling attention, eye movements and visual memory, as well as predicting subjective properties of images (like image memorability). Her research integrates knowledge and tools from image processing, image statistics, computer vision, human perception, cognition and neuro-imaging (fMRI, MEG).