Prof. Revie has over two decades of research experience in the area of epi-informatics, a term he coined to describe, “the use of informatics techniques – such as machine learning, data-driven modelling and semantic technologies – to better understand and manage disease”, and has published over 150 peer-reviewed papers in the area. Over this period there have been major changes in the ways that scientists collect, organise and reason with data, from genomic to environmental scales, to improve health in human and animal populations. As the scale and complexity of these data have increased so has the need to apply techniques from AI and machine learning to allow computers to support scientists in their bid to understand and make use of the data. Prof. Revie’s research involves active engagement with colleagues in the life sciences across a range of application domains: from data-driven models for parasite control in salmon aquaculture, to ontology-based methods for EU food-safety laboratories, to smartphone-based disease diagnosis in rural developing economies.