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Thesis Title: Characterising mobility diversity using dyadic analysis
Primary Supervisor: Ed Manley
Second Supervisor: Jens Kandt
Start Date: September 2018
Biography
My research area is primarily on mobility data. In particular, I am always looking out for different means to explore and visualise mobility data. Joining areas such as connectivity, public transport provision, demographic distribution and travel behaviour, I am trying to understand and influence to make cities cleaner and more equitable.
Aside from being a part-time PhD student in CASA, I also work in Transport for London to help planning public transport services in London. I am passionate about social equality and working hard to support the provision of the rail and bus services to everyone in London. Previously I have studied in Oxford and Royal Holloway.
Research Summary
My research is to extract deep descriptive understanding from observed mobility data by treating travel travel locations like different friends in a social network. Rather than studying the attributes of entities individually, dyadic analysis technique focuses on the nature of the relationship between two entities. Through the close study of all the relationships exist within a mobility network, I want to be able to describe the different types of relationships between locations, and how these relationships change over time.
I will use different temporal, spatial and longitudinal attributes to examine various open source observed origin-destination datasets to demonstrate the dyadic framework. This new perspective will offer alternative insights in the real-life travel behaviours. Such understanding will help enhancing mobility prediction models, the evaluation of existing mobility systems and the functions of cities.
Research Themes
Mobility, origin-destination matrix, dyadic analysis, social equality, diversity