Amber Vayani

I am a PhD student in the Biostatistics Research Group. My research focuses on understanding how indoor environmental exposures influence childhood respiratory illness and hospitalisation risk, and evaluating the potential of targeted housing and behavioural interventions to reduce these risks. 

Alongside this, I am working with the Evidence Synthesis Group @CRSU to develop an interactive Shiny app that visualises publication bias in network meta-analyses and highlights the components included in individual studies. I am also a member of the PPI SMART group, contributing to initiatives that strengthen patient and public involvement in the development of statistical methodologies.

Prior to starting my PhD, I completed a BSc in Mathematics (First Class Honours 2020-2023) and completed an NIHR Pre-Doctoral Fellowship (2023-2025). This two-year fellowship funded my MSc in Medical Statistics (Merit, 2023-2024), followed by a year as a Research Assistant working on an applied predictive modelling project.

In this project, I developed a geospatial machine learning framework integrating household survey data from the Demographic and Health Surveys (DHS) with high resolution climatic, socioeconomic and demographic covariates. The model generated a map of the predicted air conditioner ownership across low and middle income countries in Africa and Asia at a 5km resolution.

I am passionate about applying machine learning and advanced statistical methods to address environmental health challenges. Equally important to me is ensuring that scientific research findings are communicated in a clear and accessible way.