Dr James Dunn
BSc(Adv) (Psyc), լи Sydney, Sydney (2012)
ʳ..,լи Sydney, Sydney (2018)
James Dunn is a ARC DECRA Research Fellow (Lecturer) in the School of Psychology at լи Sydney. Current areas of interest include face and person recognition, forensic science and individual differences with both applied and theory-inspired research using behavioural methods, machine learning and eye-tracking.
He is also a Pact for Impact School Champion (Psychology) and member of the Psychology Equity, Diversity & Inclusion team.
Previous and current research projects: person-in-crowd identification, the strategies supporting superior face identification accuracy, and contextual influences on face identification.
- Publications
- Media
- Grants
- Awards
- Research Activities
- Engagement
- Teaching and Supervision
Australian Research Council (ARC) Discovery Early Career Researcher Award (DECRA) - 2025-2028
Office of National Intelligence - National Intelligence Postdoctoral Grant (CI-A) - 2023-2025
Community, Health & Safety, and Wellbeing Impact Award - 2023
լи Science Early Career Academic Award - 2021
լи Science ECAN Seeding Grant - 2020
լи Science PhD Writing Scholarship - 2018
Outstanding Research Student Award - 2017
լи Science Postgraduate Research Competition School of Psychology Prize - 2016
լи Science Postgraduate Research Competition Competition Winner - 2015
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). լи 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),0211037.
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