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Efficient Bayesian computation for stochastic collective cell spreading models

New insights into biological processes such as skin cancer spread and wound healing can be obtained through collective cell-spreading experiments.These experiments involve placing cells in a dish and observing how the population of cells evolve under a variety of experimental treatments and conditions by taking images and using image processing tools.An important component for obtaining insight into these processes is the biological modelling and subsequent calibration of the model to real experimental data.Cells move and proliferate, give birth to other …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

Forecasting mosquito populations in response to meteorological variables

Being able to forecast changes in disease-carrying mosquito populations as a result of changes in rainfall and temperature would provide a powerful tool to public health bodies and also allow for more efficient application of biological control strategies.The invasive mosquito, 'Aedes aegypti', predominantly inhabits urban landscapes and is responsible for the spread of diseases such as Dengue, Zika and Chikungunya.It’s populations tend to decline during the cooler months and vary in the warmer months in response to rainfall events.Recent biological …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

Spatio-temporal statistical modelling of mosquito movement through urban landscapes

The invasive mosquito 'Aedes aegypti' predominantly inhabits urban landscapes and is responsible for the spread of diseases such as Dengue, Zika and Chikungunya, but little is known about how this mosquito moves between houses and neighbourhood blocks in search of a mate and food.Mark-release-recapture experiments have been used in the past to study the dispersal of female mosquitoes in north Queensland and to estimate important movement parameters. These experiments involve marking mosquitoes with coloured dust, releasing them into a landscape …

Study level
PhD, Master of Philosophy, Honours
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

Topics in Computational Bayesian Statistics

Bayesian statistics provide a framework for a statistical inference for quantifying the uncertainty of unknowns based on information pre and post data collection.This information is captured in the posterior distribution, which is a probability distribution over the space of unknowns given the observed data.The ability to make inferences based on the posterior essentially amounts to efficiently simulating from the posterior distribution, which can generally not be done perfectly in practice.This task of sampling may be challenging for various reasons:The posterior …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

Privacy-Preserving Process Analytics

Modern organisations consider data to be their lifeblood. While the importance of data science and the potential benefits of data analytics are widely acknowledged, many people have grave concerns about irresponsible use of their data.Negative publicity surrounding large collections of personal data (incl. location, videos, pictures, emails, etc.) by corporations such as Google and Facebook and subsequent breaches have resulted in people losing trust in, and becoming more suspicious about, how their personal data is being used by such organisations.Process …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

Responsible Analytics of Process Data

Technological advances in the field of data science empowers organisations to become ‘data-driven’ by applying new techniques to analyse large amounts of data. The potential benefits include a better understanding of business performance and more-informed decision making for business growth. However, a key roadblock to this vision is the lack of transparency surrounding the quality of data.Process mining is a specialised form of data-driven process analytics where process data, collated from the different IT systems typically available in organisations, is …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

Robotic Process Automation: Research Opportunities

Recently, there has been a strong interest in industry in a specific area of automation Robotic Process Automation (RPA). This term can include robotics, software agents acting as human beings in system interactions, and process automation, workflow management systems or systems that are process-aware.RPA is a relatively new technology comprising of software agents called `bots' that mimic the manual path taken by a human through a range of computer applications when performing certain tasks in a business process. The tasks …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

Opportunities and challenges faced in intelligent transport systems

With the advancement in technology, new sources of transportation data, including traffic and transit data, have emerged which can potentially facilitate and even revolutionise transport modelling and simulation.My research team focuses on various aspects of the exploitation of emerging data for network planning, operations, management and control. This includes:new insights in travel behaviour modelling, traffic state estimation and predictiontransit network monitoring, modelling or controlapplying data from connected and autonomous vehicledata-driven operation of transportation systems with artificial intelligence and machine learning …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

An novel data-driven structural optimisation method for engineering and science

Structural optimisation, an effective design method for light-weight and high-performance structures, traditionally relies on the computational mechanics method with empirical constitutive model of related material. However, the empirical constitutive modelling remains an open question worldwide for a long term. The imperfect knowledge of constitutive laws and empiricism and arbitrariness of constitutive modelling process limit the applications of structural optimisation methods in advanced material structures.

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
Science and Engineering Faculty

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