Currently I am a principal researcher at Gradient Institute where I research and implement ethically aware machine learning algorithms and systems.
The majority of my research has been on probabilistic machine learning algorithms. This includes creating variational inference methods for Bayesian machine learning, and more recently using probabilistic techniques to measure and optimise for fairness in regression settings. I have also been involved in the creation and maintenance of a number of machine learning code-bases, see my project page for more details.
Previously I researched probabilistic algorithms for the automatic, unsupervised interpretation of data (without human training), such as underwater imagery of the seafloor obtained by autonomous underwater vehicles (AUVs).
I finished my PhD in July 2013 with the marine systems group at the Australian Centre for Field Robotics, which is in the University of Sydney. I also spent six months as a research associate with this group. I have a Bachelor of Engineering (Mechatronics, honours 1) and Bachelor of Commerce (Finance), also from the University of Sydney.