AI-generated content detection and localization

About the Project

Supervisory Team: Dr. Zhiwu Huang

In a world increasingly dominated by AI-generated content, this PhD project will research advanced AI methodologies for detection and localization of manipulated imagery. You’ll push the frontiers of computer vision and data forensics, creating tools that strengthen digital authenticity, security, and global trust in visual information.

This PhD project will push the boundaries of AI-generated content detection and localization, rapidly advancing fields at the intersection of AI, computer vision, and digital forensics. With synthetic media and image manipulation becoming ever more convincing, verifying where an image was captured and whether it is genuine, has become a critical challenge for national security, media integrity, and public trust.

The research will tackle the central problem of authenticating visual content without relying on metadata, developing innovative AI techniques to interpret visual and contextual cues such as landscape, architecture, lighting, and environmental patterns.

By integrating geospatial analysis with deepfake detection, this project aims to create robust, explainable tools capable of identifying falsified or fabricated imagery and tracing its likely origin.

Key outcomes will include:

• new explainable AI models
• comprehensive evaluation of developed geolocation and detection approaches
• practical frameworks that enhance confidence in digital evidence

The project will also contribute valuable insights into the ethical, technical, and operational implications of using AI in high-stakes image analysis. You will receive specialist research training and work within a collaborative environment, with access to state-of-the-art computing facilities and potential opportunities to engage with industry partners.

This PhD project offers a unique opportunity to contribute to the next generation of digital authenticity, geospatial intelligence, and information security research.

Entry Requirements

You must have a UK 2:1 honours degree or its international equivalent, with a strong foundation in mathematics.

You should have:

• programming skills
• a passion for research

Experience with machine learning and computer vision will be beneficial.

Fees and Funding

We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students.

Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants.

Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants.

Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.

For more information, please visit our postgraduate research funding pages.

How to Apply

Apply now

You need to:

• choose programme type (Research), 2026/27, Faculty of Engineering and Physical Sciences
• select Full time or Part time
• choose the relevant PhD Electronic & Electrical Engineering (7092)
• add name of the supervisor in section 2

Applications should include:

• research proposal
• your CV (resumé)
• 2 academic references
• degree transcripts to date
• English language qualification (if applicable)