Dr James Dunn
BSc(Adv) (Psyc),UNSW Sydney, Sydney (2012)
ʳ..,UNSW Sydney, Sydney (2018)
Dr. James Dunn is an ARC DECRA Research Fellow and Lecturer in the School of Psychology at UNSW Sydney. His research focuses on face and person recognition, forensic science, and individual differences, using advanced methodologies such as behavioral methods, machine learning, AI and eye-tracking. Dr. Dunn's work bridges the gap between theoretical research and practical applications, particularly in high-stakes environments where accurate cognitive assessments are crucial.
He is also aPact for Impact School Champion (Psychology) and member of the Psychology Equity, Diversity & Inclusion team.
Research Interests
- Face and Person Recognition:I study how we identify and remember faces and people, which is important for things like security and law enforcement. Faces tell us who people are and how they feel, and recognizing them is a complex skill that humans have evolved to do very well.
- Improving Forensic Science:My work helps make forensic science more accurate and fair, which is crucial for solving crimes and ensuring justice. I collaborate with key industry and government partners, including the Australian Federal Police and NSW Police, to develop tools and strategies that enhance accuracy and fairness in areas like identity verification and criminal investigations.
- Exploring Individual Differences:I look at why people perform differently on cognitive tasks, such as memory and attention, and what these differences mean in everyday life. This research is vital for understanding how stress impacts cognitive function, particularly in professions where memory accuracy can have significant consequences.
- How Diverse Experiences Shape Face Recognition in Humans and AI:This project aims to understand how unique experiences contribute to expertise in face recognition using computational AI models. By exploring how different experiences affect our ability to recognize faces, we can develop AI that mimics these human skills. The expected outcomes include improved accuracy and fairness in face recognition, which is crucial for security, policing, and the justice system.
Broader Impact
Dr. Dunn's research has significant applied importance, especially in enhancing accuracy and fairness in identity verification, criminal investigations, and forensic science. He is also deeply invested in the implications of his findings for AI systems, aiming to reduce biases and improve the reliability of automated processes that mimic human cognitive functions. By addressing the challenges posed by individual variability in cognitive performance, his work provides essential insights for improving decision-making processes in sensitive domains.
- Publications
- Media
- Grants
- Awards
- Research Activities
- Engagement
- Teaching and Supervision
Australian Research Council (ARC) Discovery Early Career Researcher Award (DECRA) - 2025-2028
Royal Society Te Apārangi Marsden Fund2024-2027
Office of National Intelligence - National Intelligence Postdoctoral Grant (CI-A) - 2023-2025
Early Career Impact Award - 2024
Community, Health & Safety, and Wellbeing Impact Award - 2023
UNSW Science Early Career Academic Award - 2021
UNSW Science ECAN Seeding Grant - 2020
UNSW Science PhD Writing Scholarship - 2018
Outstanding Research Student Award - 2017
UNSW Science Postgraduate Research Competition School of Psychology Prize - 2016
UNSW Science Postgraduate Research Competition Competition Winner - 2015
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
Growns, B., Dunn, J. D., Helm, R. K., Towler, A., Mattijssen, E., & Martire, K. A. (2024). Jack of all trades, master of one: domain-specific and domain-general contributions to perceptual expertise in visual comparison. Cogn Res Princ Implic, 9(1), 73.
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.
Tagliente, S., Passarelli, M., D’Elia, V., Palmisano, A., Dunn, J. D., Masini, M., Lanciano, T., Curci, A., & Rivolta, D. (2023). Self-reported face recognition abilities moderately predict face-learning skills: Evidence from Italian samples. Heliyon, 9(3).
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.1-16.
Growns, B., Dunn, J. D., Mattijssen, E., Quigley-McBride, A., & Towler, A. (2022). Match me if you can: Evidence for a domain-general visual comparison ability. Psychonomic Bulletin & Review.
Growns, B., Dunn, J. D., Helm, R. K., Towler, A., & Kukucka, J. (2022). The low prevalence effect in fingerprint comparison amongst forensic science trainees and novices. PLoS One, 17(8), e0272338. https://doi.org/10.1371/journal.pone.0272338
Trinh, A., Dunn, J. D., & White, D. (2022). Verifying unfamiliar identities: Effects of processing name and face information in the same identity-matching task. Cogn Res Princ Implic, 7(1), 92. https://doi.org/10.1186/s41235-022-00441-2
Growns, B., Towler, A., Dunn, J. D., Salerno, J. M., Schweitzer, N. J., & Dror, I. E. (2022). Statistical feature training improves fingerprint-matching accuracy in novices and professional fingerprint examiners. Cogn Res Princ Implic, 7(1), 60. https://doi.org/10.1186/s41235-022-00413-6
Dunn, J. D., Kemp, R. I., & White, D. (2021). Top-down influences on working memory representations of faces: Evidence from dual-target visual search.Q J Exp Psychol (Hove), 74(8), 1368-1377.
Dunn, J. D., Summersby, S., Towler, A., Davis, J. P., & White, D. (2020). UNSW Face Test: A screening tool for super-recognizers.PLoS One, 15(11), e0241747.
Dunn, J. D., Ritchie, K. L., Kemp, R. I., & White, D. (2019). Familiarity does not inhibit image-specific encoding of faces.Journal of Experimental Psychology: Human Perception and Performance, 45(7), 841-854.doi:10.1037/xhp0000625
Towler, A, Kemp, R. I., Burton, A. M.,Dunn, J.D., Wayne, T., Moreton, R., White, D. (2019).Do professional facial image comparison training courses work?PLoS One, 14(2),e0211037.
Towler, A., Kemp, R. I., Bruce, V., Burton, A. M.,Dunn, J. D., & White, D. (2019). Are face recognition abilities in humans and sheep really ‘comparable’?R. Soc. open sci., 6, 180772. doi:
Dunn, J. D., Kemp, R. I., & White, D. (2018). Search templates that incorporate within-face variation improve visual search for faces.Cognitive Research: Principles and Implications, 3(37), 1-11.
White, D.,Dunn, J. D., Schmid, A. C., & Kemp, R. I. (2015). Error Rates in Users of Automatic Face Recognition Software.PLoS One, 10(10), e0139827. doi: 10.1371/journal.pone.0139827
My Research Supervision
Daniel Chu
My Teaching
PSYC1027 - Forensic Psychology:Crime, Courts and Corrections (Course Coordinator)
PSYC3301 - Psychology & Law(Course Coordinator)
PSYC2071 - Perception and Cognition (Lecturer)
PSYC1021 -Introduction to Psychological Applications (Lecturer)