Scalable Computing
Research in the Scalable group centres around systems to process data at scale and their performance.
Research group focus
Our research centres around systems to process data at scale and human performance.
From the perspective of scalable data systems, our members work in:
- technical scalable computing systems
- visualisation and visual analytics
- fairness of automated decision making
Our group provides a place where people can work across these areas and come together to collaborate with the School and the wider University.
Research impact
Our research has attracted more than £100 million in external funding to Â鶹´«Ã½ over the last few decades. This underpins dozens of cross-disciplinary projects and new facilities. National Innovation Centre for Data (NICD) Scalable scientists were pivotal in founding this £30 million centre. It is now housed in the Catalyst building, with state-of-the-art decision theatre visualisation labs.
NICD has:
- delivered 80+ collaborative projects
- helped create over 700 regional jobs
- been projected to add £742 million GVA to the North-East economy in the next 10 years
Talent pipeline
The Centre for Doctoral Training in Cloud Computing for Big Data (concluded October 2024), backed by IBM Red Hat, offered a suite of industry-informed MSc programmes. Our researchers designed data management, analysis and visualisation solutions within Mobilise-D, a 5-year Innovative Medicines Initiative project, supported by the European Union's Horizon 2020 research and innovation programme and EFPIA. The programme has members from 34 participating universities, hospitals, and industry organisations, which produced, validated and accepted digital mobility outcomes to monitor the daily life gait of people with various mobility problems. It aims to inform drug and technology development, clinical practice, precision medicine, regulatory bodies and other stakeholders.
Key collaborators
Â鶹´«Ã½ is a partner university of The Alan Turing Institute. Scalable researchers lead the Visualisation Interest Group (VizTIG) and collaborate with over 65 UK universities, global tech firms and public-sector bodies.
Group member Paul Ezhilchelvan has been acting as a Consultant at the Fortune-500, Graph Database company Neo4j on the task of building a scalable and high-performance distributed Graph database. His investigations led to establishing that a simple application of known concurrency control techniques could corrupt a graph database irredeemably due to specific graph structure attributes and then to discovering smarter alternatives that avoid injecting errors while promoting high-performance. Currently, he is developing high-throughput order protocols for Neo4j to build scalable systems that are also crash-tolerant. This consultancy has been active for the past seven years and has successfully involved three PhD students and generated around 10 referred outputs at highly reputed venues.