Data-driven studies of air quality and socioeconomic predictors of mortality

I started my PhD with Prof. Alex Archibald in October 2020. My work pulls elements from multiple STEM disciplines across Atmospheric Chemistry, Epidemiology, Computer Science and Sociology. I research the impact of air quality on human health, with particular interest in the context of social inequity in urban areas. My current research focuses on Greater London and vehicle-emitted pollutants such as nitrogen dioxide and particulates. I work with large datasets and explore the applications of machine learning techniques, such as specific types of neural networks which can handle data across detailed spatial and temporal ranges.

The various species of air pollutants have well-established long- and short-term effects on disease incidence and death rates. In addition to air pollution, social inequality has also been strongly linked to health; indeed, both factors have made headlines since the beginning of the COVID pandemic. My research aims to demonstrate the importance of taking a more holistic view of air quality and health, and highlight the devastating impact that social inequity continues to make.

UKRI Centre for Doctoral Training in the Application of Artificial Intelligence to the study of Environmental Risks (AI4ER CDT)

I am a member of the AI4ER CDT, where I completed an MRes degree in 2019-20. My project studied the association between NO2 air pollution exposure and human breast cancer incidence in London, using LSTM networks.