Researcher

Dr James Daniel Dunn

My Expertise

Face recognition

Super-recognisers

Keywords

Biography

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...view more

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.


My Qualifications

BSc(Adv) (Psyc), UNSW Sydney, Sydney (2012)

Ph.D., UNSW Sydney, Sydney (2018)


My Awards

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


My Teaching

PSYC1027 - Forensic Psychology: Crime, Courts and Corrections

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Location

Mathews Building Room 1004

Contact

+61-2-9065-1425

Videos

A conversation with James Dunn, a psychologist at the University of New South Wales, on how artificially intelligent facial recognition technology differs from the skills of a super-recognizer, hosted by Tim Leberecht, co-founder of the House of Beautiful Business.
“Using familiarity to solve the face recognition problem” - James Dunn - UNSW 2015 3MT
James Dunn (Psychology) Science and Society

For his research the human ability to recognise familiar and unfamiliar faces in different situations, which could have implications for identity checks.

This presentation was a winner in the 'Science and Society' category at the UNSW Science 1 minute thesis competition in 2015.
Are you a super-recognizer?
3 Minute Thesis Presentation
Face recognition: Research to enhance facial recognition software