2009 – 2017
My academic background is in Mathematics and Statistics. In 2012, I graduated with a B.Sc. Mathematics and Statistics from Imperial College London before embarking on a M.Sc. Applied Statistics at the University of Oxford and finally returning to Imperial to pursue a Ph.D. in Statistics.
Throughout my university education, I have been fascinated with the beauty of Mathematics as well as how it has been used to advance society with Statistics being a key discipline which brings together mathematical theory and the practical intricacies present in collected data.
2017 – Oct 2019
Malaria Atlas Project, Oxford
After completing my Ph.D. thesis on “Fundamental classes of ambit fields in space and space-time: theory, simulation and statistical inference” under the supervision of Prof. Almut Veraart and Prof. Greg Pavliotis, I was inspired to continue this journey of studying spatiotemporal modelling and its applications. It led to my first post-doc research position with the Malaria Atlas Project, then based in Oxford.
Together with the interdisciplinary Global Malaria Epidemiology team, I had the opportunity to develop spatiotemporal models to obtain malaria risk maps and estimates. These are used by World Health Organisation (WHO) and the Institute of Health Metrics and Evaluation (IHME) in their annual reports to inform policy decisions. Another highlight of my time at MAP was the collaboration with colleagues at the National Malaria Control Programme and Institut Pasteur in Madagascar on studying the seasonality of malaria using health facility data.
Oct 2019 – Present
Disaster Analytics for Society, NTU
In October 2019, I returned to Singapore where I grew up and joined the Disaster Analytics for Society lab which is led by Assistant Professor David Lallemant. Here, I have been tackling problems involving earthquake damage estimation and volcano tephra model calibration with researchers at the Earth Observatory of Singapore (EOS) and Asian School of the Environment (ASE).
My hope is to continue this work of addressing interdisciplinary problems with statistics and spatiotemporal modelling, to contribute to informing policy through evidence-based analysis.