Group Leader in Biomedical Data Science
Wearable sensors, machine learning, genomics
I am a group leader in biomedical data science at the University of Oxford. Our group develops reproducible methods to analyse wearable sensor data in very large health studies to better understand the causes and consequences of disease. For example, we have developed methods to objectively measure physical activity in UK Biobank which are now actively used by researchers worldwide to demonstrate new associations with cardiovascular disease, depression, mood disorders, and others. We have further enhanced the UK Biobank resource via the development of machine learning methods to identify sleep and functional physical activity behaviours such as walking. In addition, we have discovered the first genetic variants associated with machine-learned sensor phenotypes. This work shows the first genetic evidence that device measured physical activity might causally lower blood pressure.
Our group has also conducted research on wearable cameras, and are interested in other wearable sensors that can help better understand the causes and consequences of disease. If you are interested in joining our research group, please do get in contact.
In 2015 I was fortunate to be one of only three Marie Sklodowska-Curie Actions COFUND Award winners (selected from ~9000 EU Marie-Curie fellowship holders between ’07-’13) for contributions to health sensor data analysis. I have also contributed to the creation of guidelines on the use of mobile devices in clinical trials, in collaboration with the US Food and Drug Administration (FDA) supported Clinical Trials Transformation Initiative on “Mobile Clinical Trials”.
2015 Marie Sklodowska-Curie Actions COFUND Award (only 3 selected from ~9000 EU fellows between ’07-’13)
2015-17 British Heart Foundation Centre for Research Excellence intermediate transition fellowship
2010-13 Marie Curie postdoctoral fellowship (E.U. FP7 and Irish Health Research Board)
2005-08 Irish Research Council science PhD scholarship