Identity verification is a routine part of everyday life, occurring in contexts such as border control, airport security, law enforcement and when purchasing age-restricted products. In these situations, individuals must determine whether two facial images depict the same person (a match) or two different people (a mismatch). Despite appearing straightforward, face matching is a challenging perceptual task, with accuracy varying considerably across individuals. As face matching can be error-prone, Automated Facial Recognition (AFR) systems have been developed to assist human decision-making. While these systems can achieve high levels of accuracy, human operators are often required to review and verify their decisions.  My research explores how people make identity verification decisions when working alongside AFR systems, with the aim of better understanding human-algorithm teaming and the factors that influence performance in these combined decision-making environments. 

I am conducting research under the supervision of Dr Daniel Carragher and Associate Professor Rachel Searston.