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Honours and Minor Thesis projects

Displaying 61 - 70 of 228 honours projects.


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: 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: Ron Steinfeld

Recently, program generation and optimisation techniques have been adapted to performance critical subroutines in cryptography. Codes generated/optimised by these techniques are both secure and their performance is highly competitive compared to hand-optimised code by experts [1].

 

Primary supervisor: Chunyang Chen

Software testing is a crucial part of the software development process, ensuring that the developed software is of high quality and meets the requirements of the users. However, testing can be a complex and time-consuming task, especially when it comes to testing software in multiple languages. ChatGPT is trained in multiple languages, making it easier for understanding and detect bugs in multilingual software.

Primary supervisor: Chunyang Chen

Product teams always need to conduct a user study with real and targeted users once the product is developed to test the usability and potential bugs in the products; however, this process is always time-consuming and costly. The team may need to find people of different backgrounds, train them, and then spend time with the users when they are doing the study. Moreover, they always need to conduct several rounds of usability tests every time they iterate the product based on the feedback from the previous study or because of the new requirements from product managers.

Primary supervisor: Chunyang Chen

Jupyter notebooks have become a popular platform for data scientists to develop and test their code. However, as the number of code cells and markdown cells increase in a notebook, it can become challenging to maintain code quality and refactoring. While integrated development environments (IDEs) like PyCharm and VSCode have code assistants like Copilot, these features are not widely available in Jupyter notebooks.

Primary supervisor: Chunyang Chen

Recently, large language models (LLM) gained popularity for their emerging powerful capabilities. For example, when given appropriate prompts, they could execute a task following instructions or demonstrations. In this project, we focus on generating chain-of-thought (CoT) prompts, using a codebank filled with basic sketches, to measure LLMs’ ability in automatic debugging.

 

Primary supervisor: Amin Sakzad

IT Forensics is the art of extracting digital pieces of evidence also known as (aka) artifacts in a forensically sound manner, that is presentable to a court of law. In doing this it covers a range of conceptual levels, from high-level operating systems and computer theory down to computer networking. 
 

The specific objective(s) of this project is to look at an encrypted piece of data and distinguish what encryption algorithm is used/employed. This would benefit IT Forensics researchers/investigators attacking encrypted volumes, files, folders, etc.