Artificial Intelligence
Pursuing computing advances to create intelligent machines that complement human reasoning to augment and enrich our experience and competencies.
Project
AgentGuard: Early-Warning and Routing for Predictable AgenticAI on Azure
This project introduces AgentGuard, a monitoring and routing system designed to improve reliability and cost-efficiency in Azure-based agent workflows. By analysing early trajectory signals—such as reasoning patterns and tool usage—within the first 10–30% of an…
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Towards Robust Generalization in Agentic AI via Environment Scaling
This project addresses the challenge of enabling AI agents to operate effectively in complex, realistic environments such as web navigation, computer use, and mobile interfaces. While current models excel in structured domains like mathematics and…
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Visual episodic memory and use in agentic systems
Human intelligence is defined by the interplay of semantic and episodic memory. AI research almost exclusively develops semantic memory systems, but episodic memory has many open challenges, especially for vision. Episodic memory is the ability…
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CuRA: Culture-Conditioned Routing for Safe Agentic AI
This project tackles the challenge of cultural misalignment in AI agents, which often leads to unsafe or inappropriate behaviour in diverse, real-world interactions. CuRA introduces a dynamic routing framework that leverages specialised cultural adapters to…
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Adaptive Agentic Robotic Systems
This project focuses on creating robotic systems that can adapt and improve during deployment in dynamic, unstructured environments such as warehouses and industrial sites. It combines the reliability of classical robotics with the flexibility of…
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Agentic Verifiers: Provably Safe Test-time scaling for Reasoning Models
This project introduces a novel architecture for agentic AI systems that ensures accuracy, efficiency, and safety during reasoning. It addresses two key challenges—lack of steerability and absence of verifiable guarantees—by developing verifiers that can interject…
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Towards the Psychological Security of Agentic AI
Towards The Psychological Security of Agentic AI This project addresses the critical challenge of auditing psychological safety in agentic AI systems designed to deliver evidence-based interventions for mental and cognitive well-being. While agentic AI chatbots…
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Quantifying and Mitigating Emerging Risks in Multi-Agent Collaboration
This project investigates critical safety challenges in large-scale deployments of AI agents, focusing on privacy leakage and collusion risks in multi-agent environments. As agents collaborate and negotiate across complex tasks, they may unintentionally expose sensitive…
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From Task Solvers to Teammates: A Theory-Grounded Architecture for Advancing Collaboration Readiness in LLM Agents
This project reimagines AI agents not just as autonomous problem-solvers but as effective collaborators. It introduces a theory-grounded approach to design and evaluate Large Language Model agents for human–AI teamwork. The research develops CollabBench, the…
Group
Health Futures UK
Advancing human health through machine learning research. The Health Futures UK team pursues machine learning research in service of advancing human health and our understanding of medicine. Drawing on our expertise in medical imaging and…