Our Research

Broadly, our work in the lab can be divided into 6 overlapping themes, each encompassing one or more aspects of human-in-the-loop machine learning:

We record or obtain data of behaviour in real-world environments, to fully capture the variance and richness of natural human actions.

We take a data-driven approach to analyse the high-dimensional data we record, often across complex action spaces.

We build data-driven models from these datasets, to gain insight into human behaviour in both health and disease.

Real-World Neuroscience

Class aptent taciti sociosqu ad litora torquent per conubia nostra, per inceptos himenaeos. Morbi et sollicitudin nulla, at vestibulum dolor. Mauris aliquam dolor at mauris varius vestibulum. Nulla at interdum ante. Ut finibus suscipit leo, vel auctor erat vulputate vitae. Morbi vel est lectus. Praesent et tincidunt risus. Nulla bibendum porttitor turpis vel gravida. Duis et felis lorem. Integer iaculis pulvinar ipsum, in tristique ligula consectetur nec. Nam ut dictum nunc. Cras viverra urna eu facilisis bibendum. Class aptent taciti sociosqu ad litora torquent per conubia nostra, per inceptos himenaeos. Morbi et sollicitudin nulla, at vestibulum dolor. Mauris aliquam dolor at mauris varius vestibulum. Nulla at interdum ante. Ut finibus suscipit leo, vel auctor erat vulputate vitae. Morbi vel est lectus. Praesent et tincidunt risus. Nulla bibendum porttitor turpis vel gravida. Duis et felis lorem. Integer iaculis pulvinar ipsum, in tristique ligula consectetur nec. Nam ut dictum nunc. Cras viverra urna eu facilisis bibendum.

Publications related to this research:

Human-Robot Interaction

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Publications related to this research:

RL in Healthcare

Class aptent taciti sociosqu ad litora torquent per conubia nostra, per inceptos himenaeos. Morbi et sollicitudin nulla, at vestibulum dolor. Mauris aliquam dolor at mauris varius vestibulum. Nulla at interdum ante. Ut finibus suscipit leo, vel auctor erat vulputate vitae. Morbi vel est lectus. Praesent et tincidunt risus. Nulla bibendum porttitor turpis vel gravida. Duis et felis lorem. Integer iaculis pulvinar ipsum, in tristique ligula consectetur nec. Nam ut dictum nunc. Cras viverra urna eu facilisis bibendum. Class aptent taciti sociosqu ad litora torquent per conubia nostra, per inceptos himenaeos. Morbi et sollicitudin nulla, at vestibulum dolor. Mauris aliquam dolor at mauris varius vestibulum. Nulla at interdum ante. Ut finibus suscipit leo, vel auctor erat vulputate vitae. Morbi vel est lectus. Praesent et tincidunt risus. Nulla bibendum porttitor turpis vel gravida. Duis et felis lorem. Integer iaculis pulvinar ipsum, in tristique ligula consectetur nec. Nam ut dictum nunc. Cras viverra urna eu facilisis bibendum.

Publications related to this research:

Digital Biomarkers

At present, it takes a long time to establish if new therapy for diseases are working, as clinicians currently gauge disease progression ‘by eye’ instead of using measurable and objective methods in a real-world setting. In this arm of our research, we monitor patients’ behaviour on a 24/7 basis using smart-sensors on the 4 extremities to obtain a continuous understanding of their motor capabilities in real-life. The behavioural data, motor or otherwise, is then analysed using machine learning techniques to derive new digital biomarkers, which can capture individual variations in disease progression. This novel approach will significantly reduce the time taken to detect disease progression, potentially reducing the duration of future clinical trials.

Publications related to this research:

Human Ethomics

We work on developing a data-driven, high-resolution understanding of human behaviour.

Publications related to this research: