Distilling Data for Cost-Efficient Recommender Systems

This project aims to tackle the resource-consuming nature of current recommender systems by innovating data distillation methodologies for these systems. It expects to generate new knowledge in the intersection of data-centric AI and recommender systems. The expected outcomes include a novel data distillation platform that can condense large datasets into compact yet informative data summaries, reducing the resource consumption for dealing with data in recommender systems and embedding cost-efficiency. The benefits of these outcomes will reduce energy use and carbon emission, empower numerous small companies to harness big data intelligence for conducting personalized businesses with low costs, and foster new jobs in data management.

This is an Fellowship support scheme scholarship project that aligns with a recently awarded Australian Government grant.

The scholarship includes:

• living stipend of $36,400 per annum tax free (2025 rate), indexed annually
• your tuition fees covered
• single overseas student health cover (OSHC).

Learn more about the Fellowship support scheme scholarship.

Your application will be assessed on a competitive basis.

We take into account your:

• previous academic record
• publication record
• honours and awards
• employment history.

A working knowledge of machine learning, data science, and recommender systems would be of benefit to someone working on this project.

You will demonstrate academic achievement in the field(s) of computer science and the potential for scholastic success.

A background or knowledge of computer science or statistics is highly desirable.

This project requires candidates to commence no later than Research Quarter 1, 2026. To allow time for your application to be processed, we recommend applying no later than 30 September, 2025 30 June, 2025.

You can start in an earlier research quarter. See application dates.

Before you apply

1. Check your eligibility for the Doctor of Philosophy (PhD).
2. Prepare your documentation.
3. Contact Dr Junliang Yu (jl.yu@uq.edu.au) to discuss your interest and suitability.

When you apply

You apply for this scholarship when you submit an application for a PhD. You don’t need to submit a separate scholarship application.

In your application ensure that under the ‘Scholarships and collaborative study’ section you select:

• My higher degree is not collaborative
• I am applying for, or have been awarded a scholarship or sponsorship
• UQ Earmarked Scholarship type.

Apply now