| EPSRC Reference: |
EP/Y030826/1 |
| Title: |
UKRI AI Centre for Doctoral Training in Decision Making for Complex Systems |
| Principal Investigator: |
Alvarez Lopez, Dr M A |
| Other Investigators: |
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| Project Partners: |
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| Department: |
Computer Science |
| Organisation: |
University of Manchester, The |
| Scheme: |
Centre for Doctoral Training |
| Starts: |
01 July 2024 |
Ends: |
31 December 2032 |
Value (£): |
7,827,198
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Astron. & Space Sci. Technol. |
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Summary on Grant Application Form |
This CDT will focus on challenging aspects of developing, deploying and assessing AI and data-driven solutions for semi or complete automation of real-world systems. Such systems usually involve several decision-making agents, including humans, and typically require coordinating hundreds to thousands of decisions. The CDT will specialise in training a new generation of AI researchers with the theoretical and practical skills to develop and test new machine learning models and approaches that can efficiently cope with uncertainty in complex systems. The CDT understands systems in a broader sense, including multi-agent systems in robotics, supply chain management and team sports, to systems in scientific domains such as astronomy and molecular biology.
A consortium between the University of Manchester and the University of Cambridge will lead the CDT. It will bring together researchers in machine learning with a strong track record in developing methodologies and applying these to real-world data and domain scientists with a strong track record of data-driven learning. The consortium has significant experience in the type of translational AI research that is at the core of the CDTs vision. The team is a balanced mix of AI experts, from Turing World-Leading Researcher Fellows to early-career rising stars, domain experts from selected fields of science, decision scientists, and a diverse set of companies. The priority area for the CDT will be Science and Research, starting with three fields of research, physics/astronomy, engineering biology and materials science -- and generalising the solutions to decision-making broadly in complex systems. We will train the students with the relevant knowledge and skills such that the CDT will also contribute to AI for increasing business productivity as a cross-cutting theme.
PhD projects will be co-created between AI specialists and domain experts. During their first year, students will receive foundational training in AI and ML, relevant training in the specific field of research related to the student's project, and research training through individual and group projects. From the second year and throughout their programme, students will have access to a wider training experience in entrepreneurship and public engagement. At the same time, students will engage in cohort training activities, including journal clubs and a yearly conference. Furthermore, students will benefit from the strong institutional support around Responsible Research and Innovation and Equality, Diversion and Inclusion, already in place at both Universities.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.man.ac.uk |