Our links with the Alan Turing Institute
The CMI aims to strengthen existing connections and grow new links with the Alan Turing Institute (ATI), the UK's national institute for data science and AI.
ºù«Ӱҵ is involved in various initiatives at the Alan Turing Institute and the Institute has ongoing opportunities for engagement.
The Turing University Network
ºù«Ӱҵ is a member of the Turing University Network (TUN) - a key component of the new Alan Turing Institute strategy, which aims to change the world for the better with data science and AI.
Membership of the TUN gives the University the opportunity to engage and collaborate with both the and its broader networks.
The TUN supports the Alan Turing Institute in achieving its three ambitious goals: advance world-class research and apply it to national and global challenges, build skills for the future, and drive an informed public conversation.
ºù«Ӱҵ's membership of the TUN follows a vibrant period of community-building in data science and AI at the University and throughout the wider region in South Yorkshire.
Find out more about our community
Primary contacts:
Professor Haiping Lu, Turing Academic Lead, University of ºù«Ӱҵ
Dr Emma Barker, Turing Liaison Manager, University of ºù«Ӱҵ
Turing Research and Innovation Cluster in Digital Twins (TRIC-DT)
University of ºù«Ӱҵ academics are leading the new Turing Research and Innovation Cluster in Digital Twins.
Prof. David Wagg (Coordinating Director TRIC-DT).
Prof. Keith Worden (Co-Director for Infrastructure TRIC DT).
The TRIC-DT mission is to carry out fundamental research relating to digital twins that addresses the most urgent challenges facing society and achieves real-world impact. Digital twins offer exciting new possibilities across a wide range of sectors from health, environment, transport, manufacturing, defence, and infrastructure. By connecting the virtual and physical worlds, digital twins can better support decisions, extend the operational life of systems and services, explore different scenarios, and introduce many other efficiencies and benefits. The TRIC-DT, will work with key partners in an open and reproducible manner to democratise access to open, reproducible and trustworthy ecosystems of digital twins.