Honours and Masters project

I am seeking students doing Honours or a minor thesis in a Masters interested in working on designing Learning Analytics innovations to study classroom proxemics by analysing and visualising indoor positioning data (along with other sources of data such as audio, physiological activity and characteristics of the students).

The research challenge for this project is to curate a dataset captured in a collaborative learning setting in which teams of three students engaged in conversations and created a joint concept map. The goal is to analyse the content of their conversations and concept maps they created at a multi-touch tabletop and model the epistemic constructs reflected in both their conversations and the artefact they jointly create. Depending on the trajectory that you take, examples of the questions that such a project could investigate include:

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).

Do you play any classical music instruments, like piano or violin? Would you like to combine your advanced music skills with computer science. This project analyses classical music using computer science techniques.

Commonsense reasoning refers to the ability of capitalising on commonly used knowledge by most people, and making decisions accordingly. This process usually involves combining multiple commonsense facts and beliefs to draw a conclusion or judgement. While human trivially performs such reasoning, current Artificial Intelligence models fail, mostly due to challenges of acquiring relevant knowledge and forming logical connections between them. This project aims to develop and evaluate machine learning models for commonsense reasoning, with question answering as the key application. 

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.

Antimicrobial resistance (AMR) has posed critical challenges to global health. The World Health Organization has identified carbapenem-resistant Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacterales as the top-priority pathogens urgently to be targeted for the development of novel therapeutic options. Recently, bacteriophage therapy has attracted extensive attention owing to its potential as novel antimicrobials to combat MDR pathogens.

Today's society and its organisations are becoming ever-increasingly dependent upon Information and Communication Technology (ICT) systems mostly based in cloud data centres. These cloud data centres, serving as infrastructure for hosting ICT services, are consuming a large amount of electricity leading to (a) high operational costs and (b) high carbon footprint on the environment. In response to these concerns, renewable energy systems are shown to be extremely useful both in reducing dependence on finite fossil fuels and decreasing environmental impacts.

This project builds upon an existing safety inspection system framework, integrating augmented reality (AR), artificial intelligence (AI), and automated reporting. You will follow the framework to design, implement, and evaluate a fully functioning prototype system that supports safety inspections in real-world construction environments.

This project takes a different approach to RL, inspired by evidence that Hippocampus replays to the frontal cortex directly. It is likely used for model building, as opposed to the mainstream view in cognitive science and ML - where 'experience replay' ultimately improves policy. The predicted benefits are sample efficiency, better ability to generalize to new tasks and an ability to learn new tasks without forgetting old ones.