SCRI Research Seminar: An introduction to urban data analysis at ONS Data Science Campus; an example of evaluating COVID-19 influences at community level

Title

An introduction to urban data analysis at ONS Data Science Campus; an example of evaluating COVID-19 influences at community level

Abstract 

ONS Data Science Campus aims to promote data science across the UK government institutes and internationally for public good. This involves bridging the gap between research and practice and building capabilities on utilising the power of emerging data sources and recent developments in data science and AI.

This lecture provides an introduction and overview of some of the latest projects on urban analytics and transport modelling at Data Science Campus. It further provides a deep dive into one of the recent research projects on analyzing COVID-19 influences at community level where the potentials of fusing various data sources and utilizing Machine Learning Techniques are explored.  The study results in developing a COVID-19 risk model to evaluate risk factors at community level and their evolvement over time and a real time and short-term estimates of urban areas with the highest risk of infection.

Speaker Bio

Kaveh is a lead data scientist at the data science campus (UK Office for National statistics) in charge of three squads focusing on urban analysis and mobility, net zero and environmental externalities, and health. Kaveh's main area of research is on urban modelling and analysis. He has a PhD in land use and transport modelling form Cambridge University and has been a senior research associate at Martin Center of Research in Cambridge. In addition to his role in DSC, he is currently a visiting fellow to Cambridge University Bennet Institute for public policy.