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).

Her work is regularly featured in the scientific and popular press, in museums of Art and Science as well as in textbooks of Perception, Cognition, Computer Vision and Design. She is the recipient of a National Science Foundation CAREER Award (2006) in Computational Neuroscience, an elected Fellow of the Association for Psychological Science (APA), the recipient of the 2014 Guggenheim fellowship in Computer Science and an Osher Fellow of the Exploratorium, San Francisco. Her research programs are funded by the National Science Foundation, the National Eye Institute, Google, Toyota and Xerox. See her google scholar profile page.