My Expertise
Face recognition
Super-recognisers
Keywords
Biography
James Dunn is a ARC DECRA Research Fellow (Lecturer) in the School of Psychology at UNSW 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.
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James Dunn is a ARC DECRA Research Fellow (Lecturer) in the School of Psychology at UNSW 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.
My Grants
Australian Research Council (ARC) Discovery Early Career Researcher Award (DECRA) - 2025-2028
Office of National Intelligence - National Intelligence Postdoctoral Grant (CI-A) - 2023-2025
My Qualifications
BSc(Adv) (Psyc), UNSW Sydney, Sydney (2012)
Ph.D., UNSW Sydney, Sydney (2018)
My Awards
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
My Research Activities
Dunn, J. D., Towler, A., Kemp, R. I., & White, D. (2023). Selecting police super-recognisers. PLoS One, 18(5), e0283682. https://doi.org/10.1371/journal.pone.0283682
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. https://doi.org/10.1038/s41598-023-28632-x
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). https://doi.org/10.1016/j.heliyon.2023.e14125
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. https://doi.org/10.1177/09567976221096320
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. https://doi.org/10.3758/s13423-021-02044-2
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. https://doi.org/10.1177/17470218211014357
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. https://doi.org/10.1371/journal.pone.0241747
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. https://doi.org/ 10.1371/journal.pone.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:http://dx.doi.org/10.1098/rsos.180772
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. doi:10.1186/s41235-018-0128-1
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
Areas of supervision
Perceptual and cognitive processes that underlie face identification and expertise. Including person-in-crowd identification, the strategies supporting superior face identification accuracy, and contextual influences on face identification.
Currently supervising
Daniel Chu
My Engagement
Radio National Breakfast Show (AU) - Are you a super-recogniser?
Super-recognisers on "The Project" (Channel 10, AU; 24 Nov 2020)
All of the Mind Podcast - Super-voice-recognisers
Take the UNSW Face Test to find out if you are a 'super-recogniser'.
My Teaching
PSYC1027 - Forensic Psychology: Crime, Courts and Corrections
Publications
ORCID as entered in ROS
https://orcid.org/0000-0002-6964-909X
Videos
James Dunn is a Lecturer in the School of Psychology at UNSW 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.
Previous and current research projects: person-in-crowd identification, the strategies supporting superior face identification accuracy, and contextual influences on face identification.
