Cambridge Centre for The Alan Turing Institute - Co-Directors (x3) - Turing Research and Innovation Cluster in Digital Twins
The Alan Turing Institute
A digital twin (DT) is a virtual replica of a physical process or system that is dynamically updated using data collected from real-time monitoring of its physical counterpart. Although they originated in the engineering sciences, DTs are starting to be used to successfully approach a wide range of complex scientific and social problems, including in healthcare, environmental monitoring, urban analytics, and economics.
Digital Twins are a strategic priority for the Institute and area of research and innovation strength. Through ongoing work within the Data-Centric Engineering, Urban Analytics and AI for Science and Government (ASG) Programmes, and the Environment and Sustainability interest group, The Alan Turing Institute has established one of the largest impactful portfolios of Digital Twin research and innovation in the UK – in areas from aerospace and civil engineering to urban modelling and agricultural and environmental monitoring – supported by a total investment of more than £26M.
Building on this momentum, and supported by a further £6M investment, the Alan Turing Institute is establishing a new Turing Research and Innovation Cluster in Digital Twins (TRIC-DT) to support research and innovation at the interface of AI and DT technologies, ensuring UK leadership in these technologies. This cluster will work closely with partner organizations and coordinate activity with other national DT initiatives to extend the Institute’s substantial DT research and innovation activity, and will explicitly focus on solving significant societal challenges and generating tangible societal benefits in three interrelated areas:
- Environment and sustainability: predicting and mitigating the negative impacts of climate change
- Infrastructure: enhancing the efficiency and resilience of critical infrastructure (e.g., energy)
- Health: improving human health and wellbeing
These focus areas will provide a set of defined case study projects on which to anchor the development of interoperable software and open science tools that will help move DTs from a powerful yet bespoke technology to a more easily adoptable industrial technology. The TRIC-DT will be governed by principles of open and reproducible research and effective innovation.
This vision will be achieved by establishing knowledge exchange between a central Turing Impact Hub, and a network of collaborators across the academic, government and private sectors. The Impact Hub will support a team of funded postdoctoral research fellows, dedicated DT software engineers, research application managers, community managers and ethics advisors.