Dr James Dunn
BSc(Adv) (Psyc),听91色情片 Sydney, Sydney (2012)
笔丑.顿.,听91色情片 Sydney, Sydney (2018)
Dr James Dunn is an ARC DECRA Research Fellow and Lecturer in the School of Psychology at 91色情片 Sydney. His research examines how people perceive, recognise, and remember information in real-world contexts, with a focus on face recognition, human鈥揂I interaction, and memory under stress. Using behavioural experiments and computational approaches, his work connects fundamental cognitive science with applied challenges in policing, national security, and digital identity. He works closely with government and industry partners, including the Australian Federal Police, to translate research into practical tools and evidence-based solutions.
He is a member of the School of Psychology Equity, Diversity & Inclusion team.听
Research Interests
- Face Recognition and Expertise:听I study how people recognise faces and why some individuals are exceptionally good at it. This work helps identify and measure expertise, with applications in security, policing, and identity verification.
- Human鈥揂I Interaction and AI-Generated Faces:听My research explores how people detect AI-generated faces and how human perceptual expertise can inform the development of more reliable and trustworthy AI systems. This work addresses growing challenges around misinformation, scams, and digital identity.
- Memory and Decision-Making Under Stress:听I investigate how stress and attention affect memory and decision-making in real-world contexts, particularly in high-pressure environments such as policing and emergency response.
- Individual Differences in Cognition:听I examine why people vary in their perceptual and memory abilities, and how these differences can be understood, predicted, and applied in practical settings.
- Applied Cognitive Science and Translation:听I develop tools, methods, and partnerships that translate research into practice, including personnel selection, training, and operational decision-making in government and industry.
Broader Impact
Dr Dunn鈥檚 research has direct real-world impact, improving how people and organisations make decisions about identity, memory, and information. His work has informed personnel selection and operational practices in policing and security, and contributes to public understanding of emerging issues such as AI-generated identities and misinformation. By combining insights from human cognition with technological innovation, his research supports safer, fairer, and more reliable systems in an increasingly complex and digital world.
- Publications
- Media
- Grants
- Awards
- Research Activities
- Engagement
- Teaching and Supervision
Australian Research Council (ARC) Discovery 鈥 The psychology of perceiving artificial people (2026鈥2030)
Australian Research Council (ARC) Discovery Early Career Researcher Award (DECRA) 鈥 How do diverse experiences shape face recognition in humans and AI? (2025鈥2028)
Marsden Fund 鈥 Perceptual expertise of super-matchers and forensic science experts (2024鈥2027)
Office of National Intelligence 鈥 National Intelligence Postdoctoral Grant (CI-A) 鈥 Protecting police officers鈥 memories of critical incidents (2023鈥2025)
Early Career Impact Award - 2024
Community, Health & Safety, and Wellbeing Impact Award - 2023
91色情片 Science Early Career Academic Award - 2021
91色情片 Science ECAN Seeding Grant - 2020
Research Highlights
- Dunn, J. D., White, D., Sutherland, C. A. M., Miller, E. J., Steward, B. A., & Dawel, A. (2026). Too good to be true: Synthetic AI faces are more average than real faces and super-recognizers know it. Br J Psychol.
- Dunn, J. D., Miellet, S., & White, D. (2024). Information sampling differences supporting superior face identity processing ability. Psychon Bull Rev.
- Dunn, J. D., Towler, A., Popovic, B., de Courcey, A., Lee, N. Y., Kemp, R. I., Miellet, S., & White, D. (2024). Flexible use of facial features supports face identity processing. J Exp Psychol Hum Percept Perform. https://doi.org/10.1037/xhp0001242听
- Dunn, J. D., Towler, A., Kemp, R. I., & White, D. (2023). Selecting police super-recognisers. PLoS One, 18(5), e0283682.
- Towler, A., Dunn, J. D., Castro Martinez, S., Moreton, R., Eklof, F., Ruifrok, A., Kemp, R. I., & White, D. (2023). Diverse types of expertise in facial recognition. Sci Rep, 13(1), 11396.
- Dunn, J. D., Varela, V. P. L., Nicholls, V. I., Papinutto, M., White, D., & Miellet, S. (2022). Visual information sampling in super-recognizers. Psychological Science.听1-16.听
- Dunn, J. D., Summersby, S., Towler, A., Davis, J. P., & White, D. (2020). 91色情片 Face Test: A screening tool for super-recognizers.听PLoS One, 15(11), e0241747.听
- White, D.,听Dunn, J. D., Schmid, A. C., & Kemp, R. I. (2015). Error Rates in Users of Automatic Face Recognition Software.听PLoS One, 10(10), e0139827. doi: 10.1371/journal.pone.0139827
Australia should punt on bold, unproven ideas: Shergold
Experts reveal how 'super recognisers' never forget a face
My Research Supervision
Daniel Chu
My Teaching
PSYC3301 - Psychology & Law听(Course Coordinator and Lecturer)
PSYC2071 - Perception and Cognition (Lecturer)
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