Ashwini is a Research Associate at the Institute and joined in April 2019. She gained her PhD in Statistics at the University of Glasgow and her thesis was titled "Nonparametric clustering for spatio-temporal datasets". This thesis focussed on the development of a flexible Bayesian model that identifies contiguous clusters in a data-driven manner and is able to accommodate varied (spatial, temporal and network) dependency structures. Previously, she also earned a M.S. in Biostatistics from the University of Minnesota, Twin Cities, a B.Sc. in Mathematics with Economics from the University of East Anglia and a Diploma in Economics from the University of London.
She is currently affiliated with the Health programme at the Institute and appreciates the collaborative nature of associated projects. Her research interests in this domain are diverse and include machine learning and causal inference with particular focus on subgroup identification, characterisation and variable selection.