Honours and Masters project

Generative AI chatbots are increasingly being adopted in higher education to support student learning and provide timely responses to questions. Within the Faculty of Information Technology at Monash University, AI-powered chatbots have been integrated into Ed Discussion (Ed Forum) for several units to assist teaching teams in managing online discussions and supporting student engagement.

Game-based learning is increasingly used in Computing education to encourage active participation, collaboration, problem-solving and application of technical and professional knowledge. Activities can range from low-cost classroom games such as Jeopardy-style quizzes, Bingo and team challenges to sophisticated digital simulations in which students make decisions and experience their consequences.

Teamwork is a critical graduate capability in computing education, yet students often receive little meaningful feedback about how they collaborate until a project has finished. This limits opportunities for teams to identify issues early, improve their collaboration, and develop teamwork skills throughout the semester.

This is a Summer Student Research Internship advert, running for 10-12 weeks over the summer break.

There is scope for this work to continue as an honours or minor thesis project afterwards. If you are interested in that, particularly the immersive visualisation side, please get in touch.

(Note that summer and winter student internships must be applied for here: https://www.monash.edu/study/fees-scholarships/scholarships/summer-winter)

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This project develops a distributed digital twin framework for smart grid data monitoring and analytics. The research focuses on simulating and emulating smart grid environments to enable real-time monitoring, intelligent data processing, and predictive analytics. By integrating distributed computing, digital twin technology, and adaptive resource management, the framework aims to improve the scalability, reliability, and efficiency of smart grid operations while supporting data-driven decision-making and proactive system maintenance.

This project aims to develop a lightweight YOLO-powered digital twin framework for real-time air traffic monitoring using airport surveillance cameras. The research investigates how computer vision techniques can be integrated into a digital twin capable of representing aircraft locations, movement trajectories and traffic flow in near real time.

LearnLens is an inclusive adaptive agentic AI learning system designed to support students while they learn complex and unfamiliar concepts. Its central purpose is to measure and support how learning develops, rather than evaluating students mainly through a final answer, program, circuit, assessment submission, or completed product.

This project asks how quantum and hybrid quantum-classical optimisation can be used not just to solve energy management problems more efficiently, but to solve them in ways that are fair, transparent, and usable by real people. The student will build simplified sustainable energy scheduling and resource allocation models as QUBO problems, then solve them with classical and quantum-inspired methods using Qiskit.

Motivation: The Unseen Bedrock of Modern Life

Cybersecurity and cryptography are the invisible, essential foundations of the modern digital world. Every day, billions of transactions and communications rely on complex mathematical puzzles to ensure confidentiality, integrity, authenticity, privacy and even more security features.

This project aims to develop an explainable epidemiology system that combines generative AI, biostatistics, and epidemiological reasoning to support healthcare analysis and decision-making. The system will take structured health data as input, analyse it multimodally, and build a knowledge base that can be queried by epidemiologists and health researchers.