A new research programme will develop new ways of extracting useful information from particular types of huge, complex datasets.
The programme, run by six universities including Imperial College London, will receive £6.3 million in support.
The aim is to achieve a step change in the modelling and analysis of vast banks of ever-growing, often interconnected data relating to customer needs and behaviour and the performance of systems and equipment, for instance.
We aim to [...] help tackle some of the challenges faced by our increasingly interconnected societies.
Professor Almut Veraart
Across many sectors, this will make it easier to pinpoint problems and opportunities, make accurate predictions and plan robustly. For example, it will help tackle cybercrime and increase resilience and carbon reduction in the electricity sector.
Combining expertise in statistics, probability theory and data science, the six-year programme is being funded by the Engineering and Physical Sciences Research Council (EPSRC), part of UK Research and Innovation (UKRI).
The Network Stochastic Processes and Time Series (NeST) partnership involves six universities - Imperial College London, Bath, Bristol, Oxford, York and the London School of Economics and Political Science - and a range of companies and government organisations.
At Imperial, the project is led by Dr Ed Cohen , Professor Nick Heard , Professor Almut Veraart and Professor Guy Nason , all from the Department of Mathematics.
Professor Veraart said: "We are excited by our collaborative work on NeST. Complex datasets encompassing a network structure are ubiquitous in our everyday lives and include, amongst others, traffic, energy, social, financial and computer networks and networks of medical data.
"We aim to advance the modelling, simulation, statistical inference, learning, prediction and anomaly detection of such datasets and help tackle some of the challenges faced by our increasingly interconnected societies."
National centre of world-class expertise
The ambition is for NeST to establish itself as the world’s leading research centre in the development of new theory, methods and computational techniques for tackling the mathematical and statistical analysis of datasets generated by ’dynamic networks’.
These include not just IT networks, big and small, but also networks in the wider and more traditional sense, such as the railway network and all the railway lines and connection points (e.g. stations, where the network connects with customers) that this incorporates.
The dynamic aspect of networks is particularly important: most datasets are not static but are constantly evolving and growing.
Producing solutions by numbers
This maths research has multiple potential fields of application and is targeting, for example:
- More secure, greener power grids : Greater use of renewables is key to the UK’s energy security and its ability to achieve net-zero carbon emissions. Integrating intermittent energy sources such as wind and solar requires sophisticated forecasting of net demand on power networks. NeST will develop computer models and simulations that help meet this challenge.
- Better detection of cyberattacks : In 2022, cybercrime cost global businesses, consumers and governments an estimated £1 trillion. Innovative tools are urgently needed to make IT networks safer. NeST will develop new ways of analysing network traffic to pinpoint tell-tale changes indicative of cyberattacks, enabling earlier detection and reducing damage caused.
- Improved mail services: Mail companies face many logistical challenges to enhance the efficiency of their services. NeST will help them match resources to changing demand and better utilise their distribution infrastructure and vehicle fleets. Benefits will include improved services for business and the public, plus significant cuts to carbon footprints.
Jane Nicholson, EPSRC Director for Research Base, said: "The NeST programme demonstrates the fundamental importance of the mathematical sciences to important sectors such as energy, transport and cybersecurity.
"The team’s work in establishing itself as a leader in the study and exploitation of dynamic networks, which will reflect the fact that the data which underpin these critical sectors is constantly changing, will deliver benefits for industry and key services which impact on our daily lives."
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