This group has been formed to promote both fundamental and applied research into intelligent pervasive data processing and modelling systems.
Our researchers and collaborators come from multidisciplinary academic areas, industry and international partners. Our work has been funded by bodies such as InnovateUK and the Newton Fund, with impact through KTPs and registered patents.
Many social, political and economic structures can be understood through bottom up computational methodologies such as agent-based modelling for decomposing these systems into their various actors and components, modelling their characteristics, and interaction behaviours.
These models are based on both real and increasingly virtual world data sources which are fraught with uncertainties pertaining to noise, human decisions, knowledge perception, reliability, trust and levels of agreement between stakeholders. These sources of uncertainties can be managed and handled using fuzzy and probabilistic representation, aggregation and reasoning methodologies.
New developments in top down algorithms such deep learning approaches can be used to model real world and simulated processes to emulate complex patterns and correlations in dynamic and historical data that can also be used for empirical validation and estimation.
Advances in evolutionary algorithms can be developed for assessing and optimizing policies and strategies in terms of simulating their impact on aspects such as labour and employability modelling complex negotiation processes and improving the syntactic, semantic and search capabilities of evolutionary algorithms for handling multifaceted real-world problems.
These computational techniques can be applied to understand population mobility, economic growth, social behaviour, human sentiment, wellbeing, security and political risk, education, welfare, geopolitics and environmental concerns.
This artificial intelligence project will combine natural language processing with machine learning to develop a software system that can process routine healthcare documentation, freeing staff time for more complex cases.
This Knowledge Transfer Partnership with Mediterranean Shipping Company will develop simulation and modelling tools that will use historic data to improve decision making within the business.
We are working with facilities management organisation Cloudfm to develop an innovative self-learning IoT system that offers end-to-end lifetime care of assets for clients.
Run in partnership with Yuan Ze University and National Taiwan University Hospital, this project aims to develop intelligent drug delivery systems that can be used during surgical procedures.
This project aims to develop a modelling tool for use in predicting the impact of policy strategies on the Saudi Arabian labour market.