EPSRC Reference: |
EP/P020720/1 |
Title: |
Inference, COmputation and Numerics for Insights into Cities (ICONIC) |
Principal Investigator: |
Girolami, Professor M |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Mathematics |
Organisation: |
Imperial College London |
Scheme: |
Programme Grants |
Starts: |
01 June 2017 |
Ends: |
18 March 2019 |
Value (£): |
2,964,066
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EPSRC Research Topic Classifications: |
Numerical Analysis |
Statistics & Appl. Probability |
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EPSRC Industrial Sector Classifications: |
Aerospace, Defence and Marine |
Construction |
Transport Systems and Vehicles |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
There are many interesting open questions at the interface between applied mathematics, scientific computing and applied statistics.
Mathematics is the language of science, we use it to describe the laws of motion that govern natural and technological
systems. We use statistics to make sense of data. We develop and test computer algorithms that make these ideas concrete. By bringing these concepts together in a systematic way we can validate and sharpen our hypothesis about the underlying science, and make predictions about future behaviour. This general field of Uncertainty Quantification is a very active area of research, with many challenges; from intellectual questions about how to define and measure uncertainty to very practical issues concerning the need to perform intensive computational experiments as efficiently as possible.
ICONIC brings together a team of high profile researchers with the appropriate combination of skills in modeling, numerical analysis, statistics and high performance computing. To give a concrete target for impact, the ICONIC project will focus initially on Uncertainty Quantification for mathematical models relating to crime, security and resilience in urban environments. Then, acknowledging that urban analytics is a very fast-moving field where new technologies and data sources emerge rapidly, and exploiting the flexibility built into an EPSRC programme grant, we will apply the new tools to related city topics concerning human mobility, transport and infrastructure. In this way, the project will enhance the UK's research capabilities in the fast-moving and globally significant Future Cities field.
The project will exploit the team's strong existing contacts with Future Cities laboratories around the world, and with nonacademic stakeholders who are keen to exploit the outcomes of the research. As new technologies emerge, and as more people around the world choose to live and work in urban environments, the Future Cities field is generating vast quantities of potentially valuable data. ICONIC will build on the UK's strength in basic mathematical sciences--the cleverness needed to add value to these data sources--in order to produce new algorithms and computational tools. The research will be conducted alongside stakeholders--including law enforcement agencies, technical IT and infrastructure providers, utility companies and policy-makers. These external partners will provide feedback and challenges, and will be ready to extract value from the tools that we develop. We also have an international Advisory Board of committed partners with relevant expertise in academic research, policymaking, law enforcement, business engagement and public outreach. With these structures in place, the research will have a direct impact on the UK economy, as the nation competes for business in the global Future Cities marketplace. Further, by focusing on crime, security and resilience we will directly improve the lives of individual citizens.
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Key Findings |
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Potential use in non-academic contexts |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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.imperial.ac.uk |