Scholarship-supported research project

Generative AI-driven multimodal framework for pavement crack detection and road safety assessment

Australian Catholic University (ACU) is offering one full-time PhD scholarship package to undertake research to develop an integrated framework that leverages generative AI to evaluate road safety conditions.

This PhD project focuses on developing an integrated framework that leverages generative artificial intelligence (AI) and experimental sensing techniques to detect pavement cracks and evaluate road safety conditions. Cracks in road surfaces are a major contributor to traffic accidents, infrastructure deterioration, and costly maintenance. Early and accurate detection of these faults is essential for improving road safety and enabling data-driven infrastructure management. The project aims to combine generative AI models (such as GANs and diffusion models) with real-world experimental data obtained through high-resolution imaging, non-destructive testing, or 3D scanning methods.

The PhD candidate will work on training AI models to not only detect and classify cracks but also simulate potential safety scenarios under varying environmental and traffic conditions. These AI outputs will be validated through experimental testing and field data, ensuring that the models are both accurate and practically deployable.

Key research areas may include:

• Development of generative AI algorithms for pavement crack detection and risk prediction
• Integration of image-based AI methods with physical sensor data (e.g., vibration, strain, acoustic)
• Design and implementation of experimental protocols to validate AI outputs in laboratory or field settings
• Creation of a decision-support tool for road authorities to prioritise maintenance and enhance safety

The PhD candidate will work closely with a multidisciplinary team, including experts in mechanical engineering, civil infrastructure, AI, and transportation safety. Collaboration with industry partners will provide access to real-world data, testing facilities, and opportunities for practical deployment of the research outcomes. This project offers an exciting opportunity to contribute to safer and smarter transport infrastructure using advanced technologies. The candidate will receive training in AI development, experimental design, and interdisciplinary research methods, with opportunities for co-authored publications and industry engagement.

How to apply

Applications close: Friday 25 July 2025, 11:59 pm AEST

Eligibility

• This opportunity is open to domestic and international applicants.
• The eligibility criteria for the PhD program at ACU can be found in the Higher Degree Research Regulations.
• The eligibility criteria for research scholarships can be found in the ACU Research Training Program Scholarship Policy.

Application process

To be considered for this scholarship, applicants must submit all documentation required for an application to the PhD program at ACU, as detailed in the How to Apply instructions, plus:

• A CV detailing relevant academic and practical experience; and
• A cover letter detailing demonstrated interest and/or experience in the program of research described.

When completing the PhD application form, please indicate that you are also applying for a stipend scholarship and include the name of this project "Generative AI-driven multimodal framework for pavement crack detection and road safety assessment".

Before you apply

Interested candidates should contact Associate Professor Eila Erfani before applying for the PhD program and scholarship.