UK AI Hubs National Public Engagement Challenge 2026
The UK AI Hubs National Public Engagement Challenge invited PhD students and postdoctoral researchers from across the UKRI AI research community to communicate their work through a compelling three-minute video designed for a public audience.
The challenge was created to celebrate the depth and diversity of AI research taking place across the UK, while supporting early-career researchers to strengthen their communication and public engagement skills.
Following training and video development, participants produced short videos that explain their research, why it matters and how it connects to wider social, scientific, environmental and technological challenges.
Explore the videos below to discover the range, creativity and impact of AI research taking place across the UK. All videos are available to watch on YouTube.
Abdulrahman Almijlad
Role: PhD Student
AI Research Hub / Institution: EDGE AI Hub
Talk Tile: Safer Than Us
Research Summary:
Abdulrahman studies how to assess the trustworthiness of autonomous vehicles by linking safety, cybersecurity, data quality and AI perception. His work develops an ontology-based framework to help explain hidden risks and improve understanding of how failures in one part of a vehicle’s system can affect the whole.
Adebayo Daniel Omotola
Role: PhD Student
AI Research Hub / Institution: National Edge AI Hub for Real Data
Talk Title: Should Babies Die Because No One Was Watching?
Research Summary:
Adebayo is developing a battery-less AI monitoring device for newborn care in under-resourced hospitals. Designed to run on ambient light and process information locally without transmitting images, the system aims to provide early alerts while protecting privacy and supporting faster clinical intervention.
Bradley Stanley-Clamp
Role: PhD Student
AI Research Hub / Institution: Intelligent Earth, UKRI AI CDT in AI for the Environment
Talk title: Can AI models predict in a changing climate?
Research Summary:
Bradley explores new AI approaches for climate science that can better handle the non-stationary nature of climate change. His work aims to move beyond conventional physics-informed methods towards models that learn physical structure from observational data and support more effective climate understanding and prediction.
Eva Maria Hita Sogor
Role: PhD Student
AI Research Hub / Institution: APRIL AI Hub
Talk Title: Unconventional Computing Techniques for Power- Constrained
Research Summary:
Eva works at the intersection of AI, electronics and algebraic topology. Her research explores whether Sheaf Neural Networks could help automate the optimisation of digital circuits, reducing design time and cost while improving efficiency in the development of low-power electronic systems.
Kazu Hatta
Role: PhD Student
AI Research Hub / Institution: AI4CI Hub
Talk Title: AI’s effect on Political Radicalisation
Research Summary:
Kazu studies how AI chatbots can influence political attitudes and behaviour. His research explores whether certain conversational patterns used by commercial AI systems may shape opinions on divisive issues such as immigration, with implications for understanding political radicalisation and the broader relationship between humans and AI.
Mahdis Tourian
Role: PhD Student
AI Research Hub / Institution: AI4CI Hub
Talk Title: Can we trust AI to help nature recover?
Research Summary:
Mahdis explores how AI can support environmental decision-making by helping experts work with large and complex ecological evidence. Her research investigates a multi-agent evidence synthesis tool designed to organise, assess and combine fragmented information into transparent, structured outputs that support expert judgement in environmental reporting and assessment.
Michael Camilleri
Role: Research Fellow
AI Research Hub / Institution: CHAI Hub
Talk Title: If Health Record Could Talk
Research Summary:
Michael investigates whether routine healthcare records can reveal early warning signs of brain conditions long before symptoms become obvious. His research works backwards through patient histories to identify possible warning signals, while separating genuine signs of disease from patterns created by the healthcare system itself.
Mordecai Otter
Role: PhD Student
AI Research Hub / Institution: Cardiff University
Talk Title: Don’t Listen to Him, I Wrote This
Research Summary:
Mordecai studies how people respond to advice from AI in high-pressure situations. Using a simulated cybersecurity environment, his research examines whether people judge advice by its actual quality, or whether their decisions are shaped by whether the same advice appears to come from a human or an AI system.
Oliver Clarke
Role: Postdoctoral Research Associate
AI Research Hub / Institution: Erlangen AI Hub
Talk Title: Why Can’t AI See the Forest for the Trees
Research Summary:
Oliver works at the intersection of geometry, combinatorics and computation. His research explores how advanced mathematical structures can help reveal patterns in complex datasets, with future applications in machine learning for hierarchical and tree-like forms of data.
Prenika Anand
Role: PhD Student
AI Research Hub / Institution: UKRI AI CDT in Safe Artificial Intelligence Systems (SAINTS)
Talk Title: Is AI safe for ‘Grandma’?
Research Summary:
Prenika investigates the psychological safety of AI-powered assisted living technologies for older adults. Her research explores how these systems affect wellbeing, autonomy and trust, helping to inform safer and more inclusive approaches to designing and deploying AI in social care settings.
Rachael Laidlaw
Role: PhD Student
AI Research Hub / Institution: UKRI CDT in Interactive Artificial Intelligence
Talk Title: Birds of a Feather – Scaling Up Automated Wildlife Monitoring
Research Summary:
Rachael’s research helps conservationists process huge camera-trap wildlife datasets more efficiently. By clustering visually similar images, her AI-based approach can reduce the amount of manual labelling needed while still achieving strong results, helping biodiversity monitoring scale more effectively.
William Agbebakun Imoukhuede
Role: PhD Student
AI Research Hub / Institution: UKRI AI CDT in Citizen-Centred Artificial Intelligence (CCAI)
Talk Title: Who Said So?
Research Summary:
William explores how generative AI may reinforce unequal knowledge systems in Nigerian secondary education. Working with students and teachers, his research investigates how young people can engage critically with AI tools and help shape more locally grounded and culturally relevant AI futures.
Xiaoliang Wu
Role: PhD Student
AI Research Hub / Institution: National Edge AI Hub for Real Data
Talk Title: When speech AI cannot hear you When speech AI cannot hear you
Research Summary:
Xiaoliang works at the intersection of AI, speech analysis and healthcare. His research explores how explainable AI could help assess and interpret speech difficulties, supporting clearer rehabilitation monitoring and more personalised care for people with communication disorders.
Yuhan Wang
Role: Postdoctoral Research Associate
AI Research Hub / Institution: The AI Hub in Generative Models
Talk Title: Can AI help us understand how cells change over time?
Research Summary:
Yuhan explores how AI can support virtual experiments in disease biology by simulating changes across cells, tissues and organs. Her work aims to create more efficient and ethical ways to test biomedical ideas computationally before deciding which experiments to prioritise in the lab.
Yve Smith
Role: PhD Student
AI Research Hub / Institution: UKRI AI CDT in Citizen-Centred Artificial Intelligence (CCAI)
Talk Title: What do children imagine for AI in education?
Research Summary:
Yve’s research explores children’s ideas about the future of education with AI. Through workshops, creative activities and age-appropriate AI literacy, the project helps children develop informed views and communicate their hopes, concerns and priorities to the adults shaping educational technology.