PhD Candidates

Kelvin is supervised by OPTIMA CI Professor Kate Smith-Miles.

His current project focuses on probabilistic modelling and optimization to support decision-making under uncertainty in structured domains. Rehan is an OPTIMA Industry PhD student, based at Monash University node, working with our industry partner SE Water. He is supervised by OPTIMA CI Prof. Guido Tack and OPTIMA AI Dr Mario Boley at Monash University.

Hajar is a PhD candidate from the School of Mathematics and Statistics, The University of Melbourne under the supervision of Dr. Hamideh Anjom Shoaa, Dr. Mark Fackrell and Dr. Joyce Zhang.

Her research interests mainly are in Operations Research, Stochastic Optimization, Machine Learning, and Reinforcement Learning.

In her thesis project, she will develop an Integrated framework for scheduling hospital operating rooms using stochastic optimization and machine learning techniques to ensure that the resources available in Australian public hospitals are used efficiently. It is hoped that the research will be used to reduce elective surgery waiting times for public patients, improving the quality of life for many Australians.

Vaughn is a PhD candidate at the University of Melbourne, for the project “Interrogating and optimising the waterways long-term water quality monitoring network” with industry partner Melbourne Water, supervised by Prof. Kate Smith-Miles, Prof. Tim Fletcher and Dr Belinda Hatt.

Maintaining adequate water quality is an important component in supporting the ecological life that relies on rivers and streams and the social engagement with our waterways enjoyed by our communities. However, waterway water quality is under threat from many human influences ranging from urbanisation to agriculture to climate change. In such circumstances, understanding waterway water quality is important to inform intervention actions that may assist in maintaining water quality and thus supporting important ecological and social values. This project aims to investigate and develop methodologies to collect and interpret the data obtained from long-term water quality monitoring of waterways, and apply this to a case study in the Melbourne region.

Vaughn is closely linked with Melbourne Water, being on leave from his position at Melbourne Water as the Senior Aquatic Scientist – Waterways Water Quality, during this project.

Project: Time series subsequence comparison and representation methods for patient-ventilator asynchrony detection.

Winton’s current research project is to develop innovative multi-fidelity surrogate models for Bayesian optimisation, which utilise data of varying cost and accuracy to estimate the black-box objective function and constraints by exploiting the correlation between datasets. In doing so, the overall cost to collect the data can be greatly reduced without sacrificing the quality of the solution. He is supervised by Optima CI Prof. Uwe Aickelin, OPTIMA AI Dr Yuan Sun and Dr Ling Luo. His research interests are diverse, spanning machine learning, operations research, stochastic processes and blockchain.

Mary’s research is titled “A data-driven optimisation with an application of omni-channel logistics”. She is based at The University of Melbourne. She supervised by OPTIMA CIs Assoc. Professor Hamideh Anjomshoa and Dr Lele (Joyce) Zhang.

Xia Zhou’s PhD project consists of system optimization (static optimization) and user optimization (dynamic optimization) regarding improving traffic jams using incentives. He is undertaking this research at Monash University, supervised by OPTIMA CI Mark Wallace.