Michelle Morris is a University Academic Fellow in the School of Medicine at the University of Leeds, based in the Leeds Institute for Data Analytics. She is an interdisciplinary researcher with a background spanning: health informatics, geography, nutritional epidemiology and health economics. Her primary research interests are in spatial and social variations in diet, lifestyle and health and how new and emerging forms of data can be best utilised to understand these.
She leads a team focused on the use of new forms of 'big' and spatial data in health research, working closely with industry partners on food and activity data. Graduating with a neuroscience degree in 2002, she began a career in health informatics, working in a graduate position at EMIS, one of the UK's leading healthcare clinical system providers, where she gained international project management experience. She returned to study for a MSc, equipping her in statistics and epidemiology training (2009) and completed an interdisciplinary PhD investigating 'Spatial analysis of dietary cost patterns and implications for health' (2013), followed by postdoctoral positions in both nutritional epidemiology and consumer data research.
Currently, she directs the multidisciplinary ESRC Strategic Network for Obesity and has developed a diverse teaching portfolio, including spatial analytics and visualisation for health. With this unique career history she is well placed to achieve her vision to cross discipline boundaries bringing together people, data and methods to improve health through informatics - specifically combining consumer analytics with health informatics and using 'big data' to benefit patient outcomes.
Michelle's Turing related research will build upon and develop new approaches to using digital lifestyle data in health research. Digital lifestyle data might include supermarket food purchase transactions, as recorded using loyalty cards, or physical activity levels recorded through fitness trackers or wearable devices. Arguably the most important aspect of this work is understanding public opinion on the use of their information in this way. To do this, she will survey approximately 10,000 adults in the UK - for more information visit the survey at lida.leeds.ac.uk/research/lifeinfo/
As these types of digital lifestyle data were not originally collected for the purpose of health research it is important to understand if they are valuable and reliable to be used for this purpose. Therefore, Michelle proposes to validate these new data sources against the more traditional methods such as diet and activity diaries. Through collaborations with the Turing network it will be possible to apply new data science methods to these new data to generate new insights into lifestyle behaviours and related health outcomes.