Machine learning systems for real-world challenges

Our work addresses the full pipeline of AI system development, from data acquisition, through model development to system deployment.

We work closely with practitioners, domain experts and policymakers to understand and respond to the real-world challenges associated with AI deployment. Our research spans the fundamentals of machine learning methods, statistical emulation and uncertainty quantification, real-time inference and decision-making, systems design, the application of AI in science and industry, data stewardship, and AI policymaking. Find out more about current projects on our Research pages.