Lachlan Webb

The paper uses a mathematical model and Bayesian approach to infer population-level physiological parameters of sleep maturation from infancy to early childhood, identifying key changes in sleep homeostasis and consolidation.

The paper uses a mathematical model to analyze sleep patterns in infants and young children, finding developmental changes in sleep homeostasis and circadian rhythms.

This paper develops a deep learning algorithm to detect and classify artefacts in neonatal EEG signals, achieving high accuracy in identifying artefact types and clean EEG periods.