2023-24-project-catalogue

###Modelling infectious disease prevalence with AI methods and online user activity

Project ID: 2228bd1193 (You will need this ID for your application)

Research Theme: Healthcare Technologies

UCL Lead department: Computer Science

Department Website

Lead Supervisor: Vasileios Lampos

Project Summary:

Previous research has showcased that online user activity is indicative of various health-related signals. In particular, Web search and social media trends can provide timely insights about epidemics of infectious diseases such as influenza or COVID-19. My group has been sharing insights about influenza and COVID-19 based on Google search activity with UK’s Health Security Agency (UKHSA) for more than 5 years.

This project will use alternative streams of information (Web search, social media, mobility patterns) to achieve all or a subset of the following aims. We are also open to other related research ideas within the theme of this project.

We collaborate with UKHSA, WHO, Microsoft Research, and the EPSRC project i-sense. We have also support from Google that provides us with search activity trends.

The Ph.D. candidate should have a good understanding of introductory ML theory, good understanding of basic natural language processing (NLP) concepts, strong programming skills, and strong desire to become an ML/NLP expert.