Digital twins are an exciting technology that is developing rapidly in industrial engineering applications. The Alan Turing Institute Digital Twin Turing Innovation Cluster is a great opportunity to link across sectors and translate digital twin technology into healthcare, where digital twins will provide improved patient monitoring and forecasting to better diagnose patients and offer treatments in anticipation of their needs.Prof Steven Niederer, DT4Health Co-Lead (Internal and Industrial Liaison), School of Biomedical Engineering & Imaging Sciences.
05 April 2023
Professor Steven Niederer appointed to co-director team for Turing Research and Innovation Cluster into digital twins technology
The Alan Turing Institute, the national institute for data science and artificial intelligence (AI), has launched a ground-breaking Turing Research and Innovation Cluster focusing on digital twins.
The Research and Innovation Cluster, Digital Twins (TRIC-DT), aims to democratise access to emerging digital twin technology by providing open and reproducible computational and social tools for digital twin development and deployment as a national service.
A digital twin 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. Globally, digital twin technology is proving to be a powerful tool in a range of areas, and their rapid development and deployment is helping to address real-world problems.
The TRIC-DT research will explicitly focus on solving significant societal challenges and generating tangible societal benefits in:
- Environment and sustainability: predicting and mitigating the negative impacts of climate change
- Infrastructure: enhancing the efficiency and resilience of critical infrastructure
- Health: improving human health and wellbeing
Mark Girolami, Chief Scientist at The Alan Turing Institute, said “The TRIC-DT will help to democratise access to digital twin technology by providing open and reproducible computational and social tools. These tools will be available for digital twin development and deployment as a national service – freely accessible to the UK research and innovation communities. Working alongside a range of partners, the creation our first TRIC will build on the wealth of digital twin activity and investment.”
Professor Niederer joins a team of five co-directors:
- John Siddorn Associate Director (Digital Ocean, National Oceanographic Centre)
- David Wagg (Professor of Nonlinear Dynamics, University of Sheffield)
- Keith Worden (Professor of Engineering, University of Sheffield), and
- Kristine Dale (the Met Office's Principal Fellow for Data Science and Co-Director of the University of Exeter and MET office’s Joint Centre for Excellence in Environmental Intelligence)