University College London
Dr Liam Barrett is a research fellow at the UCL Ear Institute in the EvidENT team.
His research focus is on utilising large datasets from individuals with hearing loss to train machine learning models that address various issues related to hearing loss.
More about Liam’s work
Over the course of his PhD, Liam researched how machine learning models can predict moments of stuttering from speech and neural signals in individuals who stutter.
Bridging the Gap: Digitising hand-drawn hearing tests for big data research to improve hearing
Read about Liam’s research projectLiam’s hopes for hearing research
I chose to work in hearing research because it represents a perfect intersection of complex challenges and meaningful impact. My background in machine learning and speech technologies naturally led me to explore how AI can enhance hearing healthcare. The richness of audiological data, from audiograms to clinical notes, presents fascinating computational problems that require innovative approaches to unlock.
What truly motivates me is seeing how technological advances could help clinicians better serve patients with hearing loss.
By creating tools that simplify complex diagnostics, I hope my research will make quality hearing healthcare more widely available. By applying AI to digitise and analyse audiograms, we can unlock valuable clinical data from paper records that would otherwise remain unused. This could help us better understand different patterns of hearing loss and how they change over time.
As an early career researcher, RNID funding is invaluable in helping me establish independent research focused on using technology to improve hearing healthcare. This support enables me to pursue innovative approaches.
Beyond the financial support, RNID ensures my research addresses genuine needs and has pathways to real-world impact.