Kelvin Liu

PhD Candidates

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

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Nadhir Hassen

PhD Candidates

Nadhir’s general research interests are in machine learning (ML) with a focus on probabilistic modelling and optimization to support decision-making under uncertainty in structured domains. More specifically he is interested in designing approximate inference methods for generative models. The overarching goal of his research is to develop principled AI and ML solutions to accelerate engineering design and scientific discovery towards high-impact sustainability applications.His current research is motivated by real-world applications such as industrial optimization for optimal energy production and molecule design for drug discovery.
More information can be found on his website at https://nadhirhass.netlify.app/
Nadhir is an OPTIMA Industry PhD student. He is based at our University of Melbourne node, working with our industry partner AGL. OPTIMA Director Kate Smith-Miles supervises him.

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Rehan Mendis

PhD Candidates

Rehan’s project title is “Optimal placement of monitoring devices in smart water networks.” His interests lie in the fields of Data Science and Machine Learning (ML) with focus on probabilistic modelling and optimization to support cooperative and real life decision-making under uncertainty factors. Additionally, he has knowledge in statistical modelling and inference in specific areas such as generalized linear models (GLMs) and generalized additive models. His co-operative experience has improved his Python and R language skills to work with statistical models on practical applications in daily aspects.

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.

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Hajar Sadegh Zadeh

PhD Candidates

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.

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Vaughn Grey

PhD Candidates

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.

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Peter Wang

PhD Candidates

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

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Hritika Gupta

PhD Candidates

Hritika is a PhD student at the University of Melbourne. She is working with our industry partner ProbeGroup, supervised by OPTIMA CIs Prof Peter Taylor and Dr Mark Fackrell. Her research interests are in applied probability and stochastic modelling. Her PhD project is based on Call Centres as an application of queueing theory.

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Winton Nathan-Roberts

PhD Candidates

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.

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Mary Kolyaei

PhD Candidates

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.

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Xia Zhou

PhD Candidates

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.

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