Global, regional, and national minimum estimates of children affected by COVID-19-associated orphanhood and caregiver death, by age and family circumstance up to Oct 31, 2021: an updated modelling study
Juliette Unwin
Lecturer in Statistical Science
I develop methods to solve questions related to infectious disease outbreaks.
Seth Flaxman
Associate Professor
My research is on scalable methods and flexible models for spatiotemporal statistics and Bayesian machine learning, applied to public policy and social science.
Oliver Ratmann
Reader in Statistics and Machine Learning for Public Good
I develop bespoke statistical methods for public good. My group and I are particularly interested in novel Bayesian methods that harness information in viral deep sequence data, mobile phone mobility data, and time-resolved patient data to characterise the spread of infectious diseases, and to guide public health interventions.
Alexandra Blenkinsop
Postdoctoral Research Associate
My research involves using viral sequence data and patient data to characterise HIV transmission and guide public health interventions.
Samir Bhatt
Professor of Machine Learning, Statistics and Public Health
I focus on mathematical, statistical and computer science tools to answer questions in human health and biology.