Data, Knowledge and Discovery: Machine Learning meets Natural Science

Abstract

Increasingly it is data, vast amounts of data, that drives scientific discovery. At the heart of this so-called "fourth paradigm of science" is the rapid development of large scale statistical data fusion and machine learning methods. While these developments in "big data" methods are largely driven by commercial applications such as internet search or customer modelling, the opportunity for applying these to scientific discovery is huge. This talk will describe a number of applied machine learning projects addressing real-world inference problems in physical, life and social science areas. In particular, I will describe a major Science and Industry Endowment Fund (SIEF) project, in collaboration with the NICTA and Macquarie University, looking to apply machine learning techniques to discovery in the natural sciences. This talk will look at the key methods in machine learning that are being applied to the discovery process, especially in areas like geology, ecology and biological discovery.