PhD (Queensland University of Technology), BSc(Hons) (University of Queensland), BSc (University of Queensland)
Machine Learning and Bioinformatics. Professor Hogan’s interest is in the application of machine learning methods to pattern discovery problems in bioinformatics, specifically the discovery of regulatory motifs in bacteria and resulting inference of regulatory networks and their properties. Techniques vary, but much of this work has utilised Support Vector Machines with novel Kernels tailored to the problem. There are a number of open challenges in this area.
Making Sense of Sequences: Professor Hogan leads the Bioinformatics group within the Microsoft QUT eResearch Centre, with its focus on new methods for navigating and visualising large biological data sets. The team is responsible for the SilverGene and SilverMap visualisation tools, and the BioPatML pattern description language. See the URL below for details.
Modern Internationalisation and Localisation: the challenges of large scale and on-demand localisation of (usually text-based) content. Interests and projects include Localisation standards and workflow, Localisation in the Cloud and Mashups for ad-hoc Localisation and re-use.