Core expertise
Data mining
Data science
Data analytics
Machine learning
User modelling
Bioinformatics
Computational biology
Biography
Geoff is a world-renowned data scientist whose research investigates how to use data to best support effective evidence-based decision making and derive useful knowledge and insight. This spans artificial intelligence, machine learning, data mining, data analytics and big data.
Geoff developed many of the key mechanisms of support-confidence association discovery in the 1980s. His OPUS search algorithm remains the state-of-the-art in rule search. He pioneered multiple research areas, including black-box user modelling, interactive data analytics and statistically-sound pattern discovery. He has developed many useful machine learning algorithms that are now widely deployed.
Geoff is the author of the Magnum Opus commercial data mining software package, a system that embodies many of his research contributions in the area of data mining and has contributed many components to the popular Weka machine learning workbench. He is a technical adviser to Froomle, a data-science-driven recommendation engine.
Geoff is the only Australian to have been Program Committee Chair of the world’s two leading Data Mining conferences, ACM SIGKDD and IEEE ICDM. He is the recipient of numerous research and service awards, and served as editor in chief of Data Mining and Knowledge Discovery from 2005-2014.
