Multimodal Learning for Advanced Graph Data Analysis

This PhD project explores the integration of diverse data modalities, such as text, images, and sensor data, within graph structures to enhance learning and representation. By leveraging graph modeling and advanced multimodal fusion techniques, the research aims to develop models capable of capturing complex relationships and patterns across heterogeneous data. This approach addresses key challenges in fields like recommendation systems, social network analysis, and biomedical data, where multimodal information is critical. The goal is to design scalable, robust algorithms that improve prediction accuracy, data interpretation, and generalization across various real-world applications.

The Data Science (DS) Discipline at EECS has been largely responsible for UQ's rating of 5 (well above the world standard) in the last 3 consecutive Australia ERA exercises, for the field of Information Systems. It has a strong and internationally focused research culture as well as a growing portfolio of datasets and data intensive computing infrastructure capable of supporting terabyte level high performance storage and processing. DS members have advised ~100 RHD students in the last 5 years and contribute significantly to the national and international research community in various leadership roles. PhD students in DS will be well-supported with full access to the advanced computing facilities and the international collaboration network of the supervisors.

This project is supported by the Research project scholarship.

Learn more about the Research project scholarship.

You must contact the principal supervisor for this project to discuss your interest. You should only complete the online application after you have reached agreement on supervision.

Always make sure you are approaching your potential supervisor in a professional way. We have provided some guidelines for you on how to contact a supervisor.

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 multimodal understanding would be of benefit to someone working on this project.

You’ll demonstrate academic achievement in the field/s of multimodal understanding and the potential for scholastic success.

A background or knowledge of multimodal understanding are highly desirable.

To be considered for this scholarship, please email the following documents to Dr Ruihong Qiu (r.qiu@uq.edu.au):

• Cover letter
• CV
• Academic transcript/s
• Evidence for meeting UQ's English language proficiency requirements eg TOEFL, IELTS

Please note the following: Submitting the above documents does not constitute a full application for admission into The University of Queensland's PhD program. If you are selected as the preferred applicant, you will then be invited to submit a full application for admission. You can familiarise yourself with the documents required for this process on the UQ Study website.