Rate My Professor David White

Associate Professor David White is a researcher in the School of Psychology within the Faculty of Science at the University of New South Wales (UNSW Sydney). As the lead investigator of the Face Research Lab, his work centers on face perception, emphasizing individual differences in people's ability to perform face processing tasks. This research explores the perceptual and cognitive foundations of variations in face recognition performance, ranging from super-recognisers with exceptional abilities to impairments associated with brain injuries, mental disorders, and neurodegenerative conditions. White investigates both theoretical aspects, such as how the brain represents faces and the role of deep neural networks in modeling human face processing, and applied contexts where accurate face identification is critical, including policing, border security, courts, and private industry. His studies address human performance in face matching, collaboration with facial recognition algorithms, and the reliability of forensic evidence from CCTV and other images to prevent errors leading to identity theft, terrorism, or wrongful convictions.

White's career at UNSW includes supervision of projects utilizing advanced resources like eye-tracking technology, fMRI access, and a registry of participants spanning the spectrum of face perception abilities. His prolific publication record features highly influential works such as 'Variability in photos of the same face' (2011), 'The Glasgow face matching test' (2010), 'Face recognition accuracy of forensic examiners, superrecognizers, and face recognition algorithms' (2018), 'Passport officers’ errors in face matching' (2014), and 'Robust representations for face recognition: The power of averages' (2005). Recent contributions include 'Too good to be true: Synthetic AI faces are more average than real faces and super-recognizers know it' (2026, British Journal of Psychology), 'Information sampling differences supporting superior face identity processing ability' (2025, Psychonomic Bulletin & Review), 'The state of modelling face processing in humans with deep learning' (2025, British Journal of Psychology), 'Normative face recognition ability test scores vary across online participant pools' (2025, Scientific Reports), and 'Flexible Use of Facial Features Supports Face Identity Processing' (2024, Journal of Experimental Psychology: Human Perception and Performance). Additional key chapters cover topics like training face identification ability and solutions for CCTV identification challenges. His research bridges cognitive neuroscience, forensic psychology, and computer vision, advancing understanding of sensory processes, cognition, and social neuroscience.