Inference, COmputation and Numerics for Insights into Cities (ICONIC)

Lead Research Organisation: Imperial College London
Department Name: Mathematics

Abstract

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.

Planned Impact

The advances in fundamental research arising from the programme will impact academic researchers in applied/computational
mathematics, statistics and computer science; in particular those working in numerical analysis, statistical inference,
uncertainty quantification, machine learning, data science, network science, stochastic simulation, mathematical modelling, data assimilation and high performance computing. Moreover, the application-oriented results will impact colleagues in geography, urban design, architecture, transport, crime studies, politics and policy making.
Outside academia, because the project is embedded within a Future Cities framework, with emphasis on security, crime and resilience, immediate beneficiaries will include

- SMEs who develop bespoke data analytics applications for clients in local and national government, who will gain access to more insightful data analytics tools that can be customized to their needs,

- larger hi-tech companies developing complex IT solutions across multiple platforms,

- clients of these companies, including those in transport, sensors, satellite imaging, construction, energy and other
utilities, charities and governments, who will benefit from the extra efficincies and insights through improved products and services,

- companies working in tourism, event planning, sports and retail who will benefit from quantified city-level information,

- policy makers and law enforcement officers, who will be better placed to make informed decisions,

- user-communities living, working or spending leisure time in a city environment, who will experience better and safer
services.

A key aspect of the impact delivery plan is to exploit our existing, strong links with important players at the
academic/external interface. In particular, we have in-house connections with Imperial's Digital City Exchange, the Oxford Martin School's programme in Cities, in Future Technology, and in Science and Society, and Strathclyde's Institute for Future Cities. We also have very close working relationships with the UK's Future Cities Catapult, Dublin's Trinity Centre for Smart and Sustainable Cities, New York's Center for Urban Science and Progress (CUSP) and Chicago's Urban Centre for Computation and Data. These partners give an excellent mechanism for outreach to relevant stakeholders and for public engagement, with a level and scope that would not be possible from a single, isolated programme.

Girolami and D. Higham have been drivers in the ATI continuing development of an Urban Analytics research theme. ICONIC will be completely distinct from this and fully complementary, it is driven by the urgent need for fundamental research in mathematical sciences, driven by mathematical and statistical modelling challenges that form an holistic UQ pipeline. ATI is viewed as a UK organisation that can exploit and translate the novel tools emerging from ICONIC and co-engage in additional outreach and impact generation. Similarly, D. Higham's Digital Economy Fellowship, which employs the PDRA Dr Francesca Arrigo as a Data Scientist and has a focus on dynamic networks of digital interactions, has external partners such as Bloom Agency, Capita, CountingLab & Siemens, who can make rapid use of ICONIC's research outputs.

Relevant new links to external partners have also been established: see letters of support from representatives of UK Government Home Office, Metropolitan Police Service, New York Police Department, Police Scotland & West Midlands Police. In addition to shaping and stress-testing the research, these partners will also provide routes to rapid and high-value deployment.

Further, by training PDRAs, the project will deliver skilled, outward facing, future-leaders with experience of interacting with external partners. These individuals will be well placed to act as agents-for-change in shaping the UK demand for Future City Analytics in way that strengthens UK competitiveness.

Publications

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Al-Mohy A (2022) Arbitrary Precision Algorithms for Computing the Matrix Cosine and its Fréchet Derivative in SIAM Journal on Matrix Analysis and Applications

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Amestoy P (2023) Combining Sparse Approximate Factorizations with Mixed-precision Iterative Refinement in ACM Transactions on Mathematical Software

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Anderson D (2019) On Constrained Langevin Equations and (Bio)Chemical Reaction Networks in Multiscale Modeling & Simulation

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Arrigo F (2022) Dynamic Katz and related network measures in Linear Algebra and its Applications

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Arrigo F (2021) A Theory for Backtrack-Downweighted Walks in SIAM Journal on Matrix Analysis and Applications

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Arrigo F (2020) Beyond non-backtracking: non-cycling network centrality measures. in Proceedings. Mathematical, physical, and engineering sciences

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Arrigo F (2020) A framework for second-order eigenvector centralities and clustering coefficients. in Proceedings. Mathematical, physical, and engineering sciences

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Arrigo F (2019) Non-backtracking PageRank in Journal of Scientific Computing

 
Description Mathematics of Adversarial Attacks
Amount £202,126 (GBP)
Funding ID EP/V046527/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Public
Country United Kingdom
Start 01/2021 
End 12/2022
 
Title MATLAB Software for Deep Learning 
Description Scientific Computing software to accompany an expository article on the mathematics of deep learning 
Type Of Material Improvements to research infrastructure 
Year Produced 2018 
Provided To Others? Yes  
Impact Accompanying expository article has been used in several universities as the basis for classes, tutorials and reading groups on deep learning. 
URL http://personal.strath.ac.uk/d.j.higham/algfiles.html
 
Description LMS/IMA 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Invited talk at London Mathematical Society/Society for Industrial and Applied Mathematics joint meeting on 30th September and 1st October. Hosted by the ICMS (Edinburgh), addressing the theme of 'Mathematics in Human Society'.
Year(s) Of Engagement Activity 2021
URL https://ima.org.uk/17272/lms-ima-joint-meeting-2021-maths-in-human-society/
 
Description Pint of Science talk in Glasgow, 22 May 2019 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact Pint of Science is a regular public engagement initiative, with selected science speakers.
Year(s) Of Engagement Activity 2019
URL https://pintofscience.co.uk/city/glasgow
 
Description Research talk at Skolkovo 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited research talk and round table panel membership at
Trustworthy AI
5-7 July
Skolkovo, Moscow
My attendance was virtual.
Year(s) Of Engagement Activity 2012,2021
URL https://events.skoltech.ru/ai-trustworthy#content
 
Description Turing mtg 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Invited research talk at
Interpretability, safety and security in AI conference
13-15th December,
Alan Turing Institute
(virtual attendance)
Year(s) Of Engagement Activity 2021
URL https://www.turing.ac.uk/events/interpretability-safety-and-security-ai
 
Description Workshop on Data Science and Crime 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact One day workshop involving police data scientists from West Midlands, Police Scotland and ondon Met, and academics with relevant skills. Knowledge exchange and highlighting of current challenges were the key aims.
Year(s) Of Engagement Activity 2018
URL https://iconicmath.org/ds-crime-workshop/
 
Description Workshop on Data Science and Soaicl Media 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Industry/Business
Results and Impact An afternoon Workshop on Data Science and Social Media, held as part of a wekk ling Engage with Strathclyde series of events.
About 30 people attended from social media, policymaking, economics, to share best practice and learn about new developments at the intersection of Data Science and Social media.
Year(s) Of Engagement Activity 2018
URL https://www.engage.strath.ac.uk/
 
Description faculty lecture 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Postgraduate students
Results and Impact Invited faculty lecture (online)
Deep Learning: what could go wrong
April 2021
Year(s) Of Engagement Activity 2020,2021
URL https://www.youtube.com/watch?v=yVXtoizLl8U
 
Description research worksop 
Form Of Engagement Activity A formal working group, expert panel or dialogue
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact Dagstuhl Seminar on 'Higher-Order Graph Models: From Theoretical Foundations to Machine Learning' (21352)

August 29- Sep 1, 2021
Year(s) Of Engagement Activity 2021
URL https://www.dagstuhl.de/en/program/calendar/semhp/?semnr=21352