Impact AI and Data Science Research Group

London Borough of Haringey – Identifying Employment Gaps  

The Employment Gap research project, a key part of Opportunity Haringey, was carried out during 2023 by London Metropolitan University in partnership with the London Borough of Haringey. The project is part of the London Met Lab Empowering London initiative, which aims to engage the University with its community partners. The key aim of the project is to identify those groups in Haringey who suffer the highest levels of unemployment and to highlight the barriers they face in accessing jobs. It is well known that Black, Asian and minority ethnic residents, people with disabilities, young people and lone parents experience higher levels of unemployment, and this research project seeks to identify which particular groups are most affected, what the main barriers are in accessing work, and how well-existing employment advisory services in Haringey support these groups to access employment opportunities. Dr Elaheh Homayounvala was involved in quantitative data analysis.  

Data-centric approach to gender-based violence 

By employing data-driven strategies we can ensure responsible use of data in solving the important societal issues related to gender-based violence, particularly women and girls, while providing useful insights, applications and upholding ethical norms. Big data fusion, synthetic data generation and deep neural network models can be employed for analyzing and predicting gender-based violence (GBV) behaviours. Big data fusion is used to merge datasets from various sources to offer a comprehensive perspective of the factors contributing to gender-based violence. To overcome the privacy concerns and data limitations of sensitive domains such as GBV, synthetic datasets are generated which will contain data that reflects the statistical characteristics of the real-world data while protecting individual privacy. A deep neural network model is generated to estimate potential risks for gender-based violence based on socioeconomic factors, historical and demographic data.  This project is led by Professor Preeti Patel. 

SD Maps – demographic dashboard [Winner of The Big Idea Challenge 2022] 

Demographic data is a valuable and powerful asset and should therefore be readily available to everyone in the community. Our demographic dashboard with dynamic map of London is far-reaching and can provide government agencies, corporates, SMEs, startups, non-profit organisations, researchers, educators and individuals access to London-centric demographic data such as population, age, ethnicity, income, employment, education, marital status, and more through interactive dynamic maps. The dashboard has the potential to service the entire community in finding solutions to the current problems facing the City of London. For example, London boroughs can tackle unemployment rates through targeted groups. The Met Police can identify the factors influencing youth crime rates. Researchers can work in a more collaborative and multidisciplinary way by cutting across discipline boundaries, e.g. social scientist work with data scientist or life scientist by sharing their insights and findings through data. A venture company who may need to profile and segment target markets setup new business, e.g. new EV power charging point locations could be better selected based on residential data. An individual who is considering buying a home would like to have a broader insight into the surrounding areas and facilities. Non-profit organisations can access and share data with each other more readily to help people who need help. This project is led by Associate Professor Dr Qicheng Yu and Professor Preeti Patel. 

Horizon 2020 European Grant 

The Research Group, as part of a consortium of 17 EU partners, began working on the grant in August 2018. The grant is worth five million euros, distributed between 17 partners, resulting in around 326,000 euros for Emeritus Professor Hassan Kazemian's research contribution. The impact of this research is significant to the British economy, security, public health and the community, as the main initial beneficiaries are West Midlands Regional Police and Thames Valley Police. The results of the project have helped the Group contribute to new publications, underlining London Met’s standing as a centre of excellence for artificial intelligence and machine learning security research in European and world security.