Honours and Minor Thesis projects

This project relates to the visualisation of the source of data used in scientific experiments, and their results. The visualisation focus is graphs.

Trust in the results of scientific experiments and scientific modelling relies on knowing how they have been derived – that is, the ‘scientific workflow’ that led to their production. Being able to reproduce the scientific workflow that led to such results is critical in ensuring trust, confidence and transparency [2].

In our current day and age, there is an exponential growth in multimodal data, especially the transition of social media from text-based communications to video formats which can be observed with the rise of TikTok, Youtube, and Instagram Reels. This shift requires a shift in how we analyze multimodal data as we will have to move away from traditional text sentiment analysis such as TextCNN.

The application of AI in sports is widely researched as both coaches and players realise the significance of quantitative analysis that can be extracted from video matches. Detecting and segmenting in-play scenes in sport video
sequences is necessary in various applications such as quantitative game and performance analysis. In studies on video-based game and performance analysis of racket sports, much research efforts have been made to explore the relationships between predefined parameters and sports performance, and the methodologies for effective coaching.

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:

AI has been growingly 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. 

This project is in collaboration with the Faculty of Dentistry, Airlangga University, Indonesia. We will explore the use of AI in dentistry, especially in dental medical imaging and periodontology (gum disease). Gum disease often causes bone loss in the furcation of a lower molar (see picture below).

Admission to the Medical degree at Monash is very competitive. The criteria is beyond the ATAR score. It covers many other factors, such as health test, interview, etc. Consequently, the ranking process is very complex.

Are you interested in programming maps, such as GoogleMaps or Open Street Maps? This project uses online maps extensively for visualising routes, and other objects of interest.

Multimedia content such as audio, image, and video are stored and transported in compressed forms. Various standards are designed to encode the content at the highest possible level while minimizing distortion. Some commonly used compression standards include MP3 for audio, JPEG for still image, H.264/AVC for video. Despite the vast differences in signal characteristics, most compression standards have two things in common: transformed-quantized coefficients and scale factor (quantization table in JPEG and AVC). The coefficients are usually coded as a product of sign_bit and magnitude.

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).