PhD Candidates

Xinyu’s project titled “Human-Centric Approach to Sustainable Microgrid Management” aims to prioritize the role of human factors in the operation and efficiency of microgrids. By placing humans at the center of the operation and management process, this project aims to tailor microgrid operation and management strategy to better match user behavior, needs, and preferences, thus enhancing system efficiency and sustainability. He is supervised by OPTIMA AI Dr. Hao Wang, Dr. Buser Say, and Dr. Frits de Nijs.

Py is a PhD student at the University of Melbourne supervised by Dr Ellie Hajizadeh, Prof Michael Kirley and Dr Dominic Robe. Py is interested in combining various optimisation and machine-learning tools to tackle challenging problems in science and engineering. His current project focuses on applying the methods to inverse design multiscale polymeric materials with desired properties. His previous work modelled complex logistic system and developed hybrid algorithms to optimise its efficiency.

Nuwani’ s project title is “Optimal Predictor Selection for High-dimensional Nonparametric Forecasting”. The project’s primary goal is to discover more objective and principled way(s) of variable selection in a situation where there are many possible predictors to a forecasting model. Non-linear transfer function models with additivity constraints imposed, and Neural Network models are the forecasting models of interest. The studied models will be experimented with using half-hourly electricity demand data from the Australian Energy Market Operator and groundwater level data from the Australian Groundwater Explorer. OPTIMA CI Prof. Rob Hyndman supervises her at Monash University.

Lakshan has been a PhD student at Monash University since 2020 under the supervision of Dr Reza Razzaghi and OPTIMA CI Prof. Rob Hyndman. His project title is: “Data-Driven Exploration of Power System Strength”. His project concentrates on characterising and monitoring the system strength in modern power systems as inverter-based resources become more prominent. He is working on synthetic data produced by a power system simulator, and the next phase is to work with real sensor data. He aims to optimise the placement of a new technology of sensors (called non-fundamental Phasor Measurement Units) within a power grid to predict unstable dynamic phenomena that occur in weak grids.

Drew’s project is titled “Long term energy grid planning with considered fluctuating renewable sources and energy storage”. He is supervised by OPTIMA CI Andreas Ernst, co-supervised by OPTIMA AI Ariel Liebman & Pierre Lebodic.

Canchen Jiang is a PhD candidate in the Department of Data Science and AI at Monash University, Australia, under the supervision of Dr. Hao Wang, Prof. Ariel Liebman, and Dr. Edward Lam. His research interests include optimization and machine learning for electric vehicles and smart grid.

Ahmad’s project title is “Energy Storage System for Integration of Renewable Energy and Improving Reliability of Electricity in Indonesia.” He is supervised by OPTIMA AI Prof. Ariel Liebman at Monash University.