Honours and Masters project

This project is based on the paper "Academic Journals, Incentives, and the Quality of Peer Review: A Model", in which we analyse strategic interactions between scientists and science journals.  Our results shed light on how different objectives for journals shape the strategies that scientists adopt when aiming to publish their work. In this project, we aim to extend this model to include the influence of different environmental factors such as prestige, affiliations or career stage of the scientists.

Machine learning (ML) training and evaluation usually involve large-scale datasets and complicated computation. To process data efficiently, a promising solution is to outsource the processes to cloud platforms. However, traditional approaches of collecting users' data at cloud platforms are vulnerable to data breaches. Specifically, during the ML model training or inference service offering, the cloud server could learn the input data used to train the model, model structures, user queries and inference results, which may be sensitive to users or companies. 

Chatbots for mental health are shown to be helpful for preventing mental health issues and improving the wellbeing of individuals, and to ease the burden on health, community and school systems.  However, the current chatbots in this area cannot interact naturally with humans and the types of interactions are limited to short text, predefined buttons etc. In contrast, psychologists in real-world interact with patients with multiple modalities, including accustic and visual information. Non-textual information is also essential for health observation and treatments of patients.

A recommender system is a subclass of information filtering/retrieval system that provides suggestions for items that are most pertinent to a particular user without an explicit query. Recommender systems have become particularly useful in this information overload era and have played an essential role in many industries including Medical/Health, E-Commerce, Retail, Media, Banking, Telecom and Utilities (e.g., Amazon, Netflix, Spotify, Linkedin etc).

As the number of mental health patients increases, the demand for qualified counselors is on the rise. However, training/practice sessions with actual patients are often limited, let alone meeting a sufficient number of patients of different personalities. This project aims to use large language models to simulate therapy sessions under certain predefined circumstances. This project is co-supervised by a collaborator from the Psychology department in Jeffrey Cheah School of Medicine and Health Sciences.

Are you ready to dive into the future of education and revolutionise how software projects are assessed? Join this innovative project aimed at creating cutting-edge learning analytics capabilities within the Faculty of IT at Monash University. This project seeks to provide automated support for teaching staff in augmenting the marking of software development and design assignments, specifically software projects submitted to the FIT-based GIT lab platform, using advanced large language models (LLMs).

Become part of the Monash Immersive Analytics Lab, and explore exciting new ways to visualise, interact, and analyse all types of data with VR and AR! We are looking for enthusiastic students to work on immersive visualisation using latest technology, such as head-mounted displays with integrated eye-trackers (Microsoft HoloLens and others), gesture recognition devices, and large wall displays.

In the evolving landscape of data reporting, traditional text-based and quantitative methods are increasingly being supplemented by rich, community-generated qualitative data, including audio and video content. This shift presents unique challenges and opportunities in how non-profits, government bodies, and community organizations present and utilize this data.

Political polarization is a phenomenon that permeates societies worldwide, manifesting in divergent ideologies, entrenched viewpoints, and societal fragmentation. In the context of Indonesia, a diverse and populous nation with a complex socio-political landscape, understanding political polarization is crucial for fostering social cohesion and effective governance.

The Javanese language, spoken by a population of over 98 million people, faces notable challenges in digital and technological applications, especially when compared to globally recognized languages. This disparity is highlighted in several studies that discuss the lack of deep learning research benefits due to data scarcity for Javanese. Additionally, other studies have pointed out the inaccessibility of data resources and benchmarks for Javanese, contrasting with languages like English and Mandarin Chinese.