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25th February, 2022

City receives Alan Turing Institute Network Development Award

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City, University of London has been named among the first-ever successful UK university applicants to The Alan Turing Institute’s Network Development Awards.

Dr Eduardo Alonso and Dr Esther Mondragon, from City’s Artificial Intelligence Research Centre (CitAI), will lead an interdisciplinary team across the university, which includes Dr Diana Yeh from the School of Arts and Social Sciences (SASS), Dr Sara Jones from the Bayes Business School, Dr Enrico Bonadio from The City Law School, and Dr Michal Krol and Dr Andrea Baronchelli from the School of Mathematics, Computer Science and Engineering (SMCSE), to foster collaborative research into secure, ecological and inclusive non-fungible token (NFT) and blockchain technology for the creative industries.

In all, the Turing Institute’s innovative awards have been made to 24 UK universities including institutions from Scotland, Wales, Northern Ireland and England.

City demonstrated its own particular proven research excellence and a track record of translation in data science and AI. City and the other 23 outstanding applicants will now be significantly enhanced through active involvement with the Institute’s thriving network.

As the national institute for data science and AI, the Turing Institute already has a well-established network of university partners. However, these awards enable the Institute to extend its reach.

The group of successful universities will be awarded up to £25,000, to:

  • Establish or grow an engaged and diverse community working (at all career stages) in data science and AI research and innovation at the university, who are aware of and engage in the potential opportunities and initiatives available across the Turing network;
  • Identify and establish links between Institute priority areas and areas of interest and expertise at the university;
  • Host activities and initiatives that are open to the wider data science and AI research and innovation community and/or local and regional communities, to form new links and collaborations;
  • Map the university’s expertise and strengths in each of the Institute’s priority areas and those considered of national strategic importance (in data science and AI) not yet covered by the Institute;
  • Design plans for how the network will become sustainable for the future.

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