Research Themes

Computational modelling of human behaviour using multimodal machine learning, spanning individual behavioural signals, social interaction and group dynamics.

Developing interpretable AI models that recognise affective and behavioural states while explaining their decisions through meaningful, human-understandable concepts for explainable responsible AI. 

Leveraging novel multimodal machine learning to model behavioural and affective signals relevant to mental health applications and wellbeing. 

Developing state-of-the-art machine learning and computer vision models to understand animal behaviour, affective states and welfare in naturalistic and real-world settings for animal health and welfare.