We have opportunities available for PhD research in the areas of Data Science, Data Mining, Machine Learning and Deep Neural Networks, among others. Our students are supported by a range of scholarships and top-ups and receive travel support during their study.
For more general information, read about the Graduate Research Program and Scholarships.
Our PhD community is socially and professionally active, regularly coming together for lunch-time meetings as well as focussed reading groups and an annual retreat.
Current featured PhD students
Bhagya works on hospital readmission risk prediction for patients with chronic disease conditions under the supervision of Prof. Wray Buntine and Dr. Yuan-Fang Li. Her research interests include data mining, machine learning, medical risk prediction and representation learning.
Chaitanya studies prediction-making in environments that are in constant flux. In data-mining terms, he studies classification under concept drift. He is open to collaborations that explore real life applications of making predictions in complex changing environments such as financial markets, cryptocurrency mining, election analysis or sports odds. View his latest work.
Chang currently works on various Data Mining and Machine Learning projects. His thesis involves Scalable Time Series Data Mining with further research interest in Railway Maintenance and Wireless Sensor Networks.
Dai’s research interest is in applying deep learning to Natural Language Processing and Information Extraction. Under supervision of Prof. Dinh Phung, Dai is working on search personalisation, graph embeddings and representation learning in general.
He Zhao is a final-year Ph.D. student supervised by Prof. Wray Buntine and Dr. Lan Du. His research lies at the intersection of Bayesian statistics, machine learning, and data mining with applications in text analysis, social network analysis, and collaborative filtering. His research has been published in ICML, AISTATS, and ICDM. He reviews for NIPS, UAI, AAAI, and ACML.
Kasun’s research area focuses around leveraging recurrent neural networks on large scales of related time series in particular Machine learning for time series forecasting. His PhD research is supervised by Prof. Wray Buntine and Dr. Christoph Bergmeir.
Under supervision of Dr. Reza Haffari and Prof. Wray Buntine Poorya’s research interests lie at the intersection of deep learning and natural language processing. He has been awarded CSIRO’s Data61 top-up, MGE and MIPRS scholarships for his PhD course.
As a PhD student at the Faculty of Information Technology, Sameen’s research is primarily focused on using context to improve upon the current sentence-based Neural Machine Translation models.