Short Sequence Representation Learning with Limited Supervision

Project opportunity

This Earmarked Scholarship project is aligned with a recently awarded Category 1 research grant. It offers you the opportunity to work with leading researchers and contribute to large projects of national significance.

Predicting events based on short text and video data is widely found in real-world applications such as online crime detection, cyber-attack identification, and public security protection. However, developing such an effective prediction model is very difficult due to the problems such as limited supervision, heterogeneous multiple sources, and missing and low-quality data. This project is to tackle these challenges. The expected outcome of this project will lay a theoretical foundation for effective short-sequence representation learning and build next-generation intelligent systems. This should benefit our society and economy through the applications of multimodality-integrated video technologies for cybersecurity and public safety.

Scholarship value

As a scholarship recipient, you'll receive: 

  • living stipend of $32,192 per annum tax free (2023 rate), indexed annually
  • tuition fees covered
  • single Overseas Student Health Cover (OSHC)


Professor Xue Li

School of Information Technology and Electrical Engineering


Preferred educational background

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 statistics, artificial intelligence, multimodal machine learning, computer vision, and multimedia analysis would be of benefit to someone working on this project.

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

A background or knowledge of deep learning algorithms in machine learning field is highly desirable.

Latest commencement date

If you are the successful candidate, you must commence by Research Quarter 1, 2024. You should apply at least 3 months prior to the research quarter commencement date.

If you are an international applicant, you may need to apply much earlier for visa requirements.

How to apply

You apply for this project as part of your PhD program application.

View application process