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Honours and Minor Thesis projects

Displaying 1 - 10 of 219 honours projects.

Primary supervisor: Teresa Wang

A recommender system is a subclass of information filtering/retrieval system that provides suggestions for items that are most pertinent to a particular user without an explicit query. Recommender systems have become particularly useful in this information overload era and have played an essential role in many industries including Medical/Health, E-Commerce, Retail, Media, Banking, Telecom and Utilities (e.g., Amazon, Netflix, Spotify, Linkedin etc).

Primary supervisor: Lizhen Qu

Chatbots for mental health are shown to be helpful for preventing mental health issues and improving the wellbeing of individuals, and to ease the burden on health, community and school systems.  However, the current chatbots in this area cannot interact naturally with humans and the types of interactions are limited to short text, predefined buttons etc. In contrast, psychologists in real-world interact with patients with multiple modalities, including accustic and visual information.

Primary supervisor: Hao Wang

The world’s energy markets are transforming, and more renewable energy is integrated into the electric energy market. The intermittent renewable supply leads to unexpected demand-supply mismatches and results in highly fluctuating energy prices. Energy arbitrage aims to strategically operate energy devices to leverage the temporal price spread to smooth out the price differences in the market, which also generates some revenue.

Primary supervisor: Ehsan Shareghi

Large Language Models (LLMs) have revolutionized natural language processing (NLP). These models have shown an unprecedented level of knowledge and reasoning, pushing the boundaries of what is achievable in NLP. However, the use of LLMs in the real world still presents numerous difficult challenges and application of LLMs beyond simple API/Prompt calls is very under-explored.

Primary supervisor: Shujie Cui

Machine learning (ML) training and evaluation usually involve large-scale datasets and complicated computation. To process data efficiently, a promising solution is to outsource the processes to cloud platforms. However, traditional approaches of collecting users' data at cloud platforms are vulnerable to data breaches.

Primary supervisor: Julian Garcia Gallego

This project is based on the paper "Academic Journals, Incentives, and the Quality of Peer Review: A Model", in which we analyse strategic interactions between scientists and science journals.  Our results shed light on how different objectives for journals shape the strategies that scientists adopt when aiming to publish their work.

Primary supervisor: Julian Garcia Gallego

The tennis tour is a series of tennis tournaments played globally over a calendar year, where professional tennis players compete for prize money and ranking points. The structure of the tennis tour is organised into different tiers for both men and women, including grand slam tournaments and ATP/WTA tour events. In this project we use stochastic processes to model and simulate the tour under different experimental rules.

Primary supervisor: Zhaolin Chen


Magnetic Resonance Imaging (MRI) stands as a cornerstone in medical imaging, providing non-invasive, high-resolution images of the human body's internal structures.  Brain tumor segmentation from MRI scans is essential for precise diagnosis and treatment planning. MRI provides detailed views of brain structures and abnormalities, but challenges like image noise, contrast imperfections and tumor variations can make segmentation difficult.

Primary supervisor: Zhaolin Chen


The early detection of neurological abnormalities through Magnetic Resonance Imaging (MRI) is crucial in the medical field, potentially leading to timely interventions and better patient outcomes. However, the traditional diagnostic process is often time-consuming and subject to human error. This project seeks to improve this aspect by employing deep learning for anomaly detection in MRI scans, exclusively using images from healthy participants for model training [1].

Primary supervisor: Agnes Haryanto
Mental health is an ongoing issue in Australia. The cause of mental health can be due to a variety of reasons: workplace culture, high workloads, job insecurity, disparity in pay, lack of career advancement opportunities and turnover intentions. Mental healthcare workers are not able to cope with it and are suffering from burnout. There is a need to ease mental healthcare workers' workload and provide consistent patient triage with the help of technology. The project aim is to investigate the existing approaches and tools in facilitating mental health workers to perform efficient patient care…