What you'll investigate

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.

Scholarship package

The successful applicant will be awarded a scholarship package consisting of:

* International candidates only

Your research community

Principal supervisor

Associate Professor Eila Erfani

View profile

Affiliation

Discipline of Computing

The Discipline of Computing at Australian Catholic University (ACU) is a future-focused and impact-driven academic unit committed to responsible innovation and ethical technology development. We advance inclusive, interdisciplinary research that addresses some of the most pressing societal challenges of our time. Our work is closely aligned with a transdisciplinary initiative dedicated to human-centred, socially responsible, and high-impact technology solutions. Through strong collaborations with industry and community partners, we ensure our research delivers practical outcomes that benefit society. This PhD project reflects our strategic focus on applying advanced technologies to solve real-world problems. Candidates will be supported within a collaborative and inclusive research culture, with access to expert supervision, cutting-edge facilities, and meaningful industry engagement.

Industry partner

Transport for NSW

We lead the development of safe, integrated and efficient transport systems for the people of NSW. Our customers are at the centre of everything that we do, including transport planning, strategy, policy, procurement and other non-service delivery functions across all modes of transport - roads, rail, ferries, light rail and point to point.

Visit the Transport for NSW website

How to apply

Applications close: Open until awarded

Step 1: Assess your eligibility

Eligibility

Before you apply, confirm you meet the following eligibility criteria:

• 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 Policy.
• The eligibility criteria for research scholarships can be found in the ACU Research Training Program Scholarship Policy.

Conditions

By applying, you acknowledge and accept the following conditions:

• The scholarship package is subject to satisfactory progress and full-time study mode.
• The scholarship conditions align with the ACU Research Training Program Scholarship Policy.
• The successful applicant will be required to assign their intellectual property (IP) to ACU as a condition of enrolment.

Step 2: Express your interest

Interested candidates are encouraged to contact Associate Professor Eila Erfani prior to applying for the PhD program and scholarship, to express their interest and discuss the project in detail.

Email: eila.erfani@acu.edu.au

Step 3: Submit your application

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 outlining 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".
• when asked which Faculty you are applying to, please select 'ACU'.
• when asked which School/Research institute you are applying to, please select 'Computer and Data Science'.