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Found 8 matching student topics

Displaying 1–8 of 8 results

Data-driven and process-aware workforce analytics

Modern information systems in today’s organisations record massive amount of event log data capturing the execution of day-to-day core processes within and across organisations. Mining these event log data to drive process analytics and knowledge discovery is known as process mining. To date various process mining techniques have been developed to help extract insights about the actual processes with the ultimate goal to organisations' workforce capability and capacity building.As an important sub-field of process mining, organisational mining focuses on discovering …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Information Systems
Research centre(s)
Centre for Data Science

Explainable AI-enabled predictive analytics

Modern predictive analytics underpinned by AI-enabled learning (such as machine learning, deep learning) techniques has become a key enabler to the automation of data-driven decision making. In the context of process monitoring and forecast, predictive analytics has been applied to making predictions about the future state of a running process instance - for example, which task will be carried out next, when and who will perform the task, when will an ongoing process instance complete, what will be the outcome …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Information Systems
Research centre(s)
Centre for Data Science

5G and IoT smart ontology learning

This project aims to investigate privacy preservation protocols in a 5G integrated IoT environment through an analysis of the depth of smart-device use in common smart domains. 5G’s addition to IoT-based smart devices will be effectively deployed and utilised by a large majority of individual and organisation-based users. The knowledge-based ontology and tools developed in the project will help form the new privacy preservation mechanisms that are required for the 5G enabled environment.The development of an ontology for 5G enabled …

Study level
PhD, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

AI-Based Data Analysis on Multiple Imaging Modalities

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality globally. According to the World Health Organization (WHO), it is estimated CVD takes 17.9 million lives every year. In Australian, the statistical data from the Australia Heart Foundation shows CVD is a major cause of death in Australia. It occupies 26% of all deaths, responsible for an average 118 deaths every day. Four of the main types of CVD are coronary heart disease, strokes and transient ischaemic attack, peripheral …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

Data reasoning to extend domain knowledge in deep learning

A wide variety of companies now use personalized prediction models to improve customer satisfaction, for example, detecting cancer relapses, Detecting Attacks in Networks (e.g., SDN) or understanding Customer Online Shopping Behaviour. However, the dramatic increase in size and complexity of newly generated data from various sources is creating a number of challenges for domain experts to make personalized prediction.For example, early detection of cancer can drastically improve the chance and successful treatment. Recently, supervised deep learning has brought breakthroughs in …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

Assessing the quality of training

Understanding the impact that training data quality has on model generation is important for industry’s looking to engage in responsible data science.In this project we’ll look at the use of instance space analysis for assessing the quality of training data and algorithm performance.

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Data governance for process mining

Data is the new asset for organisations. Due to technological developments, organisations are faced with insurmountable amount of data. Analysis of this data provides endless transformative opportunities and contributes to the organisation's strategic decision making. However, the challenge is to derive maximum value from data.Data governance refers to a collection of practices and processes that enables an organisation to manage its internal and external data. Data governance assists in formulation of a corporate wide program that assists in making data …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Information Systems

Sampling to optimise training data

Training data is needed for fitting supervised machine learning models but may not always be plentiful, especially when labelling needs to be performed manually. In such a situation we may wish to target the new sample cases to be labelled to improve model performance for the least additional resource.In this project we’ll look at how active learning techniques - techniques which make use of the model outcomes – can be used to effectively determine a sampling strategy.

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

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