GAIL funds five new projects on AI’s impact and use

GAIL has awarded its latest round of seed funding to five innovative projects led by GAIL Fellows, supporting early-stage work in the area of Generative AI that will run until June 2026.

The schemes span healthcare, engineering biology, finance and social impact, and will culminate in a showcase event in July highlighting findings and future directions.

GAIL’s seed funding scheme is designed to help University of Edinburgh researchers test ambitious ideas, build new partnerships and secure larger external funding, strengthening University of Edinburgh’s role as a leader in the field of Generative AI.

A photographic rendering of a young houseplant against a neutral background, seen through a refractive glass grid and overlaid with an single neuron from a neural network diagram. — Alan Warburton / Better Images of AI / © BBC / CC BY 4.0

Seed-funded projects

The newly funded projects are:

Agents of Discovery: A Seminar Series on AI Scientists

Led by Professor Filippo Menolascina, School of Engineering, this series will explore “AI scientists” – autonomous systems that can generate hypotheses, design experiments and analyse data. This series brings together world-leading pioneers from industry and academia to discuss how these "AI Agents" are fundamentally reshaping the scientific method. The talks will connect informatics, engineering biology and policy, and create a digital library of public lectures on agentic AI for science.

Agentic AI in Venture Capital

Also led by Professor Menolascina in collaboration with Dr Francesco Corea from Co-Founder of Data Hunt a startup that specialises in data for venture capital, this project will pilot an executive education concept on the use of Agentic AI by venture capitalists and fund managers. The work will demonstrate how AI agents can help investors screen deals and run due diligence more efficiently, tapping into Edinburgh’s renowned expertise in fintech.

Implementation of Generative AI across Health and Social Care

Dr Lucas Seuren, Usher Institute, and colleagues will convene a cross-sector workshop with clinicians, policymakers, patient representatives and industry to examine why Generative AI tools such as clinical scribes are being deployed without robust evaluation. The project will develop a position paper on safe implementation, regulation and ongoing monitoring.

Interpretable Multi-Agent Framework for Pulmonary Health Assessment

Dr Hao Yu, School of Engineering, and team will develop a prototype AI system that combines radiation-free Electrical Impedance Tomography with CT scans to generate standardised lung health reports. By using multi-agent, multimodal large language models, the project aims to support continuous, clinically meaningful respiratory monitoring.

Can LLMs Give Relationship Advice?

Dr Tuğrulcan Elmas and his collaborator Dr Yusuf Mücahit Çetinkaya, both from the School of Informatics, will build the first large-scale, theory-grounded dataset of online relationship narratives and AI-generated advice. Using established psychological frameworks, they will benchmark how well large language models understand and respond to complex relational problems.

Supporting GAIL’s objectives

Together, these projects exemplify GAIL’s objectives to harness generative AI for public benefit, while rigorously examining its risks, limitations and societal consequences.

Professor Ram Ramamoorthy, Director of GAIL, said: “These projects demonstrate the breadth and strength of the research into Generative AI that our GAIL Fellows are undertaking. The outcomes of these projects will help guide the future direction of work at GAIL and within the University.”