I am an Assistant Professor at the National University of Singapore (NUS), where I am primarily working at the intersection of public health, machine learning, and Bayesian modelling. I am part of the Machine Learning & Global Health Network, which is a multi-country and multi-organization network focused on doing fundamental research in machine learning and problems related to global health.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. For my doctorate, I built models for understanding the evolution of popularity in social media. My work focused on algorithms to model point processes with classical machine learning techniques as well as using modern deep learning networks, mainly recurrent networks. Learn more about Swapnil Mis