/
/
/
Mr Laiton Hedley

Mr Laiton Hedley

PhD Candidate, University of Newcastle

Funded by the Defence Innovation Network to apply cognitive psychology to cybersecurity risk assessment and human factors analysis.
Published peer-reviewed research on human-machine teaming and dynamic decision-making in collaborative and competitive environments.
Volunteered with The Smith Family to support the education of disadvantaged and neurodiverse primary school students.

Laiton Hedley is a cognitive psychologist and PhD candidate at the University of Newcastle. His research focuses on how people work together in dynamic, high-pressure environments, particularly exploring human-human and human-machine teaming.
Laiton applies a combination of experimental methods, behavioural analysis, and computational modelling to investigate how workload, reward, and social context shape team decision-making and performance.

He has a strong interest in making psychological science practical and impactful, with his work contributing to applied fields such as defence, cybersecurity, and healthcare. He is especially interested in benchmarking human performance against idealised models to better understand cognitive bottlenecks and collaboration strategies.

Alongside his research, Laiton teaches undergraduate psychology at the University of Newcastle, specialising in research methods, statistics, and human cognition. He also has experience supporting students with accessibility needs and contributes to community education through volunteer work.

Laiton is passionate about interdisciplinary research and is driven by a desire to bridge the gap between theory and real-world application. His recent projects involve collaborations with defence and industry partners aimed at improving human-machine interaction and understanding the cognitive underpinnings of team behaviour under stress.

He is committed to producing rigorous, transparent research that not only advances academic knowledge but also supports safer, more effective systems for human operators across a variety of settings.