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Bayesian deep learning for incomplete information

This project will feature a synergy of deep learning, modular and multi-task learning with Bayesian methods to address the problem of decision making given incomplete information. more...

Supervisor(s): Cripps, Sally (Professor), Chandra, Rohitash (Dr)

Health burden of chronic diseases

This research project aims to model the health burden of chronic diseases and their comorbid conditions using Markov models, Bayesian statistics and Complex network. more...

Supervisor(s): Uddin, Shahadat (Dr)

Machine learning and optimisation for modelling coral reef evolution

Globally, coral reef systems are under threat from major changes in environmental parameters (e.g. sea level, sea surface temperature, pH and water quality). Forward Forward Stratig more...

Supervisor(s): Webster, Jody (Associate Professor), Chandra, Rohitash (Dr), Salles, Tristan (Dr)

Controls on the Holocene evolution of the Great Barrier Reef: linking 4D numerical modeling and observational data

This project will investigate the biological and geological processes that control the evolution of coral reef systems (e.g. reef communities, stratigraphic ages and growth rates, r more...

Supervisor(s): Webster, Jody (Associate Professor), Chandra, Rohitash (Dr), Salles, Tristan (Dr)

Semi-metric machine learning techniques to investigate trend of COVID 19 spread and impact on stock market

The spread of COVID 19 pandemic appears to occur in several phrases and each phrase has possibly different impacts on the economy as reflected in the stock market. This project aims more...

Supervisor(s): Chan, Jennifer (Associate Professor)

Magnetic Explosions on the Sun

Solar flares are magnetic explosions on the Sun, which directly affect the Earth through their influence on our local space weather. The basic process underlying flare energy releas more...

Supervisor(s): Wheatland, Michael (Professor)