Research Projects
Research projects are theoretical and aimed at generating new knowledge or insights through original research and investigation.
The primary focus for the research projects is on conducting original research and contributing new knowledge or insights to a specific field or domain, with the involvement of an academic supervisor.
The outcome that industry partners can expect is typically a research paper or a prototype that demonstrates the research findings and contributions.
Research projects are more theoretical and involve identifying a research problem, conducting a literature review, formulating hypotheses, and carrying out experiments or analyses.
The emphasis is on advancing the understanding of a particular topic or area through rigorous research and investigation.
Research projects often involve developing new algorithms, models, or techniques to address complex problems or challenges.
Computer Science Subject
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Subject Name: Computer Science Research Project COMP90078~COMP90081
Subject Coordinators:
- Semester 1- Jey Han Lau jeyhan.lau@unimelb.edu.au
- Semester 2 - Cezary Kaliszyk cezary.kaliszyk@unimelb.edu.au
Length of project: Year-Long, full time (i.e. students work on the project 100% without taking any other subjects during the 2 semester)
Subject details:
These year-long projects offer an opportunity to engage with emerging talent on complex problems that require a deep investigation in computer science research, which involves identification of an appropriate research question, planning and execution of experimental or theoretical research, synthesis of research findings and potentially develop software prototypes. Although software implementation will be involved and a prototype may be part of the deliverables, the primary outcome of the collaboration is to offer industry partner with valuable insights and knowledge derived from the research findings, which can help address intricate challenges within their operations.
Examples of Projects:
- Vision Language Models for Coastal Monitoring
- Automated Evaluation for LLM-based software development and code review
- Breath Tracking using a Depth Camera for XV Scanner
- AI-Driven Text Communication in Clinical VR
- Using robot dogs for remote space exploration and fetching objects
Computing Subjects
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Subject Name: Computing Research Project - COMP90055
Subject Coordinators:
- Semester 1 – Ting Dang ting.dang@unimelb.edu.au
- Semester 2 - Farhana Choudhury farhana.choudhury@unimelb.edu.au
Length of project: 1 Semester – Only available in Semesters 1 & 2
Subject details:
This subject offers industry partner an excellent opportunity to collaborate with high-achieving students who have scored highly in their studies. These top-tier students will conduct detailed research on significant issues within the field of Computing, AI, Distributed Computing, and Cybersecurity that require in-depth investigation. Students will potentially develop software and prototypes, with a primary focus on delivering valuable insights and innovative solutions to industry partner's challenges. This collaboration offers industry partners with high-quality research and analysis tailored to their specific needs, benefiting from the involvement of high-performing students.
Examples of Projects:
- AI-driven models of human visual cognition
- Enhancing immersion in VR with human-robot collaboration
- Distributed algorithms for knowledge graph alignment
- Multi-GPU, High-Performance Computational Algorithms for Quantum Molecular Simulations
- Cloud-Device Collaborative Learning via small and large language models for mobile health
- LLM Natural Language Processing for Digital Forensics
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Subject Name: Advanced Studies in Computing - COMP90005
Subject Coordinators:
- Semester 1 – Ting Dang ting.dang@unimelb.edu.au
- Semester 2 - Farhana Choudhury farhana.choudhury@unimelb.edu.au
Length of project: 1 Semester – Only available in Semesters 1 & 2
Subject details:
Students will carry out complex real-world challenges through research, analysis, and potentially create software and prototypes. This collaboration offers industry partners with valuable insights and innovative solutions to their specific problems, leveraging the students' research and analytical skills.
Examples of Projects:
- Advancing Spatial Queries: From Keyword-Based to Vector Search
- Interpretable Deep Learning Model for Multi-Label Review Classification
- Anomaly detection on Satelite telemetry data
- A Trustworthy LLVM Backend of the Cogent Compiler
What's next?
Subject your project proposal to work with us on the Student Industry Projects
Contact us to assist you.
- Prof Leon Sterling
- leonss@unimelb.edu.au
- Phone
- +61 3 9214 8491