Responsive representation learning for dynamic video-sharing platforms

This project investigates how machine learning models can proactively respond to rapid changes in large-scale video-sharing platforms such as evolving content trends, user behaviour, and interaction patterns.

You will develop new representation learning techniques capable of predicting, modelling, and leveraging dynamic changes in platform ecosystems. The project will explore:

-- change-aware representation learning for evolving video content
-- modelling user behaviour dynamics and community shifts
-- adaptive learning algorithms that proactively leverage platform changes
-- applications in recommendation, content understanding, and user engagement analytics.

This project will be conducted within the School of Electrical Engineering and Computer Science at The University of Queensland. The research group specialises in machine learning, data mining, and large-scale multimedia analytics.

You will work with a collaborative team researching representation learning, multimodal data mining, and AI systems for large-scale online platforms. The environment provides access to advanced computing resources, research seminars, and strong links with international academic and industry collaborators working on large-scale AI systems and digital platforms.

This project is supported by the Research project scholarship.

Learn more about the Research project 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 frameworks (e.g., PyTorch), data mining techniques, and large-scale data analytics would be of benefit to someone working on this project.

You will demonstrate academic achievement and the potential for scholastic success.

A background or knowledge of representation learning, recommender systems, or social media data analysis is highly desirable.

You must submit an expression of interest (EOI) by 16 March, 2028 16 March, 2028.

Before you apply

1. Check your eligibility for the Doctor of Philosophy (PhD).
2. Prepare your documentation.
3. If you have any questions about whether the project is suitable for your research interests, contact Professor Helen Huang (huang@itee.uq.edu.au).

When you apply

To apply, submit an expression of interest (EOI) for the program. You don't need to apply separately for the project or scholarship. How to submit an EOI

In your EOI, complete the ‘Scholarship/Sponsorship’ section with the following details:

1. Are you applying for an advertised project: 'Yes'
2. Project: 'Research project scholarship'
3. Scholarship Code Listed in the Advertisement: VIDEOSHARING-HUANG
4. Link to Scholarship Advertisement: https://study.uq.edu.au/study-options/phd-mphil-professional-doctorate/projects/responsive-representation-learning-dynamic-video-sharing-platforms

Submit an EOI