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Department of Computer Science and Technology

Monday, 7 September, 2020 - 15:00 to 16:00
Aiden Doherty (Nuffield Department of Population Health, University of Oxford)

Abstract: TBD

Bio: Aiden Doherty is a group leader in biomedical data science at the University of Oxford. His 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, they 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. They 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, the group has 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.

In 2015 Aiden was 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. He has 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”.

Seminar series: 
Centre for Mobile, Wearable Systems and Augmented Intelligence Seminar Series