I am a Florence Nightingale Research Fellow and I develop methods for modelling infectious diseases in resource-limited settings, with an overall objective to advance scientific understanding, inform policy, and benefit global health. 

Throughout this research, a key question is understanding when, where, and why infectious diseases spread. To respond and plan accordingly, decision-makers need such information in a timely and reliable manner. The power of modelling lies in the ability to provide such information, and therefore, I focus on methods that can i) learn from the past, ii) monitor the present, and iii) plan for the future.

Often focusing on climate-sensitive infectious diseases in low- and middle-income countries, I develop interdisciplinary methods which blend theory and knowledge from across maths, statistics, and AI. These methods often integrate heterogeneous models, data, and theory from across branches of science, and are grounded in practical public health objective of providing actionable information for decision-makers. 

Mathematical biology, global health,  mosquito-borne diseases, forecasting and forecast evaluation