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Theme 3 - Enhancing syndromic surveillance for early detection of incidents
University of East Anglia
Odie is a PhD student at the University of East Anglia, Norwich with Public Health England. He completed a BSc in Software Engineering and an MSc in Advanced Computing at the University of East Anglia.
His main area of interest is applying machine learning to formulate or augment data mining algorithms. His PhD focuses on syndromic surveillance using web and social media data. Syndromic surveillance is the real-time (or near real-time) collation, interpretation and dissemination of public health data to allow the identification of potential public health threats and their impact, enabling public health action. His project investigates the feasibility of enhancing such systems with data obtained from social media (e.g. Facebook or Twitter) or other data sources available on the web.