Tom Blau is a PhD student at the Faculty of Engineering and Information Technologies. His research focuses on using reinforcement learning when training robotic arms to perform object manipulation tasks. He is especially interested in using Bayesian methods to improve exploration, as well as training in simulation in order to accelerate learning for real-world policies.
Rafael is a PhD student at the Faculty of Engineering and Information Technologies. He is interested in the problems stemming from planning under uncertainty. In many scenarios, a solution to a planning problem has to be determined without the full knowledge of factors such as internal dynamics or planning objective. Rafael applies Bayesian optimisation to solve these types of problems. He is currently working on how to use Bayesian optimisation methods to solve planning problems in robotics where uncertainty is inherent.
Nicholas is a PhD candidate in the School of Mathematics and Statistics. His research focuses primarily on Bayesian nonparametric methods for the analysis of non-stationary multivariate time series, with a particular focus on spectral analysis. Although mostly theoretical, his research has been applied to make inference on crime, health and financial time series.
Tin began his PhD the Faculty Engineering and Information Technologies in 2018. He is interested in reinforcement learning and robotics. His research aim is to enable artificial intelligence to learn policies directly from high-dimensional sensory inputs and make value judgments based on spatial and temporal scales.
Matthew began his PhD in machine learning in 2017. The purpose of Matthew’s research is to find ways of applying machine learning techniques to high dimensional, non-linear systems and large datasets. Matthew hopes his research will enable better prediction and control of non-linear dynamical systems.
Philippe started his PhD at the University of Sydney in 2015 in the School of Information Technologies. His research interests include exploration in reinforcement learning and decision-making in uncertain environments, with applications to robotics.
Harrison is a PhD student concentrating on the area of machine learning. In his research, he’s found that when it comes to neuroscience, machine learning is difficult due to the lack of data. His research examines methods that will collate and augment datasets in order to improve the statistical power of neuroscience experiments and machine learning models.
Sheila is a PhD student in the School of Information Technologies. Her research focuses on how wearable devices can help the elderly and disabled population. As part of her research, she also examines the constraints of wearable technology.
Ransalu's research interests cover spatiotemporal modelling, dynamical systems and robot learning. He works on estimating uncertainty in phenomena that change in space and time.
Louis is a PhD student in the School of Information Technologies. He is interested in building on implicit probabilistic models in machine learning and applicability of variational inference. His work aims to advance new techniques in this field to provide a better theoretical understanding of newly-proposed approaches.
Anthony is a PhD student in the Faculty of Engineering and Information Technologies. His research interests focus on approximate and generalised kernel methods for large-scale Bayesian modelling, variational methods, and automated complex pattern discovery and extrapolation. The application of his research spans robotics, spatio-temporal modelling, and automated process discovery. He also works with industry in investigating reinforcement learning methods in healthcare.