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Honours and Minor Thesis projects

Displaying 1 - 10 of 240 honours projects.

Primary supervisor: Daokun Zhang

AI is revolutionizing drug discovery by significantly reducing economic costs and accelerating the drug development process. We are collaborating with the Faculty of Pharmacy and Pharmaceutical Sciences (ranked #1 in 2022 and #2 in 2023 globally according to the QS World University Rankings by subject) to explore the application of advanced AI methodologies in drug discovery.

Primary supervisor: Delvin Varghese

Podcasts have become a very popular way for small communities to create content that is meaningful for them and reach a wider audience. However, many of the skills and equipment needed to produce a good podcast are inaccessible to non-professionals and there is often a learning curve attached to gain necessary skills. In addition, the production process is seen as an individual effort (one or two producers working in isolation to produce the final edit).

Primary supervisor: Delvin Varghese

Radio is one of the primary modes in which communities across the world receive important information and build connection with wider society. Non Governmental Organisations (NGOs) have long been leveraging radio, and in particular Community Radio


In many parts of the world, audio is the preferred interface for social interactions. There has been a huge push towards audio-based interfaces for engaging marginalised communities in rural and Developing countries contexts.

Primary supervisor: Delvin Varghese

As part of this project, you will work closely with a community organisation or NGO (this can either be an organisation that you have existing links with or we will connect you with one of our partner NGOs). Working in collaboration with the org, you will find out challenges they face in giving voice to their communities/beneficiaries that can be addressed through social media (for instance, perhaps they want to run an awareness raising campaign about the difficulties faced by the community and they want the communities to be very involved in this).

Primary supervisor: Delvin Varghese

Traditionally many organisations prefer to work with text-based reports based on quantitative data collection.

These reports are used to share their insights and practices within their organisation, with other organisations, with donors and with community members.

In recent years, community generated qualitative data, in the form of audio or video content is more widely becoming a mode of data collection for organisations.

Primary supervisor: Lizhen Qu

This project is within the scope of the project “Artificial Intelligence in carDiac arrEst” (AIDE), which was led by Ambulance Victoria (AV) in Australia, involving a team of researchers at Monash University. This AIDE project has developed an Artificial Intelligence (AI) tool to recognise potential Out-of-Hospital-Cardiac Arrest (OHCA) during the Triple Zero (000) call by using transcripts produced by Microsoft Automatic Speech Recognition service.

Primary supervisor: Zachari Swiecki

Note that this project is available as an undergraduate winter scholarship project

Primary supervisor: Pari Delir Haghighi

The goal of this project is to develop an IoT application that generates IoT queries based on IoT situations. The queries will be generated dynamically, as the state of entities or situations will change. This project will focus on IoT technologies and situation inference/awareness concepts.

Primary supervisor: Pari Delir Haghighi

Current methods for generating health related recommendations mostly apply machine learning, rule-based methods or AI models. Generative AI (using Large Language Models) is receiving a great deal of attention and popularity due to its capabilities to not only understand and generate natural language responses but also to analyse and reason. Generative AI tools such as ChatGPT provide an exciting opportunity for generating health related recommendations.

Primary supervisor: Bohan Zhuang

Equipped with the self-attention mechanism that has strong capability of capturing long-range dependencies, Transformer based models have achieved significant breakthroughs in many computer vision (CV) and natural language processing (NLP) tasks, such as machine translation, image classification and so on. However, the good performance of Transformers comes at a high computational cost. For example, a single Transformer model requires more than 10G Mult-Adds to translate a sentence of only 30 words.