Augustine is a doctoral candidate based at the Big Data Institute and the Experimental Medicine Division. His work explores the intersection of infectious diseases, genomics and data science, with an emphasis on antimicrobial resistance (AMR).
Augustine's current research uses machine learning in conjunction with genomic and clinical data for culture-free prediction of AMR. His work aims to optimise antibiotic selection, identify new AMR determinants and contribute to the understanding of resistance mechanisms and the evolution of AMR in pathogens. He is also investigating the application of genomic information in antimicrobial stewardship for more effective infection prevention and control strategies.
Augustine received his medical degree from the University of Hong Kong, followed by a Master’s in Applied Digital Health from Oxford. His DPhil project is generously supported by the University of Oxford and the Croucher Foundation.
