I am an Assistant Professor at the Saw Swee Hock School of Public Health, and joint appointments at Institute of Data Science, and Department of Statistics and Data Science. My research focuses on applying and developing statistical machine learning techniques for the broader and messier world of science and public policy, especially global health. I develop flexible and scalable models for understanding various spatiotemporal data, for example, epidemics (COVID-19, Malaria, HIV) and crime.

My contributions to COVID-19 pandemic modeling, Bayesian inference, computational social science and machine learning earned the prestigious NUS Presidential Young Professorship (PYP) in 2024, NRF Fellowship in 2023, the Blackwell-Rosenbluth Award in 2022, and the SPI-M-O Award for Modelling and Data Support in 2022. In 2022, I co-founded the Machine Learning & Global Health Network, a collaborative initiative spanning three continents that brings together researchers to address global health challenges.