AI-Driven Detection of Misinformation Propagation in Healthcare Systems

About the Project

Applications are invited for a self-funded, 3-year full-time or 6-year part time PhD project.

The PhD will be based in the School of Computing and will be supervised by Dr Elisavet Andrikopoulou and Dr Aikaterini Kanta.

The work on this project will:

• Combine healthcare, cybersecurity, and AI to develop targeted, credible counter-narratives optimised for virality and trust.
• Models health misinformation spread using cutting edge frameworks to identify transmission patterns and high-risk nodes.
• Designs AI-generated agents that engage in online spaces to subtly disrupt or dilute false narratives without detection.
• Validate the AI models in synthetic environments to assess their effectiveness.

Health misinformation is not just a public health issue but also a national security one. The lines between cyber attacks and information warfare are blurring. AI is used both to spread and to fight misinformation. We need better tools on the defense side. Current fact-checking systems are reactive and weak on trust modeling and community dynamics.

This project aims to investigate how misinformation spreads through healthcare-related channels, such as social media, forums, patient platforms, or electronic health records, how it undermines public trust and system security, and design AI-based models that (1) detect it early, (2) predict its propagation pathways, and (3) introduce subtle disruption mechanisms to counter it.

Research objectives:

• Characterise misinformation vectors in healthcare (platforms, users, topics, tone).
• Model propagation patterns using graph-based and agent-based AI.
• Correlate misinformation surges with cybersecurity vulnerabilities (for example, ransomware targeting hospitals during information chaos).
• Evaluate effectiveness with real-world datasets and simulate controlled misinformation campaigns.
• Synthetic persona injection: Use AI agents to subtly steer or dilute misinformation in a community (controversial, but cutting-edge).

This project pushes the boundaries of ethical AI by deploying synthetic personas as subtle counter-influencers, raising critical questions around manipulation, trust, and digital autonomy. It blends outbreak modeling with real-time intervention strategies, using agent-based simulations, LLM-driven dialogue systems, and graph analysis to test how misinformation spreads and how it can be quietly contained. The experimental framework includes simulating infodemics in sandboxed environments, deploying adaptive agents, and evaluating impact across virality, engagement, and trust metrics.

Fees and funding

Visit the research subject area page for fees and funding information for this project.

Funding availability: Self-funded PhD students only.

PhD full-time and part-time courses are eligible for the UK Government Doctoral Loan (UK and EU students only).

Bench fees

Some PhD projects may include additional fees – known as bench fees – for equipment and other consumables, and these will be added to your standard tuition fee. Speak to the supervisory team during your interview about any additional fees you may have to pay. Please note, bench fees are not eligible for discounts and are non-refundable.

Entry requirements

General admissions

You'll need a good first degree from an internationally recognised university (minimum upper second class or equivalent, depending on your chosen course) or a master’s degree in computer science or a related area. In exceptional cases, we may consider equivalent professional experience and/or Qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

Specific candidate requirements

• Skills and experience in machine learning and programming
• Ability to work independently and collaboratively within a multidisciplinary team.
• Knowledge of cybersecurity topics and/or health informatics.

How to apply

We’d encourage you to contact Dr Elisavet Andrikopoulou (elisavet.andrikopoulou@port.ac.uk) to discuss your interest before you apply, quoting the project code.

When you are ready to apply, please follow the 'Apply now' link on the Computing PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process.

When applying please quote project code: CMP10231026