Are you interested in applying your database knowledge to a medical domain? In this project, you will explore data curation, management, processing and analysis of medical data. You will explore various medical and patient datasets available publicly, such as the UK Biobank, Cancer Atlas, etc.
Honours and Masters project
Displaying 1 - 10 of 262 honours projects.
AI and Music
Are you interested in applying your AI knowledge to music, especially classical music? You will explore how AI (and Deep Learning) can be used in music, such as using Generative AI to create Theme & Variations in classical music, analysing classical music structures (e.g., sonata form, theme & variation form, etc.), and identifying instruments (e.g., violin vs. viola).
AI in Medicine
AI has been increasingly used in Medicine. There are big opportunities for AI in medical research, including medical imaging diagnosis. AI and Deep Learning have been used to detect and classify lesions in various diseases, such as cancers.
Explainable AI (XAI) in Medical Imaging
Are you interested in applying your AI/DL knowledge to the medical domain? This project focuses on the use of AI in Medical Imaging (e.g., CT, MRI, X-ray, ultrasound). The work includes segmentation and classification; for example, segmenting tumour from medical images and then classifying the tumour grade. We will use various Deep Learning techniques, such as CNNs, and experiment with a variety of Deep Learning frameworks, such as U-Net and ResNet.
Historical Map of Melbourne
This project aims to develop a historical map of greater Melbourne, showing its yearly road development and residential land use from 1966 to the present. You will learn how to use a geospatial DBMS and a geospatial visualisation tool.
Bioinformatics and Data Science
Are you interested in biomedical? You could combine your data science and computing expertise to analyse DNA and genetics.
Quantum Data Processing
Are you interested in learning Quantum Computing from scratch? If yes, this project might be for you. Week by week, you will explore and learn the basics of quantum computing, focusing on data processing. You will answer questions such as what the limits of classical computing are, why new paradigms are needed, and where quantum computing may help.
Bundle Recommender Systems with Large Language Models
Bundle recommendation systems enhance user experience and increase sales by recommending a set of items as a bundle rather than individual items [1]. The understanding of items in bundles is that they should be complementary some how. In this project, we will explore the relationship between causal reasoning on items purchased and bundles. Causal reasoning could be used to infer if two purchases are related, and, moreover, language language models can be used to assess the plausability of this, to help create an argument using the Bradford-Hill criteria. Some recent research has…
Identifying Assumptions in Research Papers using AI
AI is starting to be used for reviewing in international AI conferences. For instance, http://paperreview.ai as announced by Andrew Ng as an “Agentic Reviewer” trained on ICLR 2025 reviews, and Google is field testing an AI-based Paper Assistant Tool for authors submtting to NeurIPS 2026. Significant research is going into developing these tools, and some good test data exists collected from previous conferences. In this project we will work with the VinUniversity AI group who is developing a benchmarking framework for evaluating AI reviewing. Research papers usually contain important…
Truth-Seeking with Language Models
It is said that ChatGPT is ‘not trying to be right, it’s just trying to be plausible.’ While the LLM community talk about hallucination, it is a complex phenomenon and a product of their construction. The training and theory of LLMs has no notion of truth, they generate text with no critical evaluation of content or sources. Many text sources are opinions, some may have subtle or not so subtle propaganda, some reflecting misinformed views, and LLMs reproduce this mess. Moreover, the training and theory of LLMs has no notion of epistemic uncertainty, they have no sense of uncertainty. …