The Data Impact Fellows programme is designed to support the use of UK Data Service data and resources by new generations of researchers and analysts working in the academic sector and, for the first time, in UK registered charities.
This year’s applications for the 2023 round of the Data Impact Fellows programme were of extremely high quality, making the judges‘ job extremely difficult. After much deliberation, it was decided to make seven awards.
We’ll be hearing more from each of the Fellows over the year, in this post they give a brief introduction to themselves and their research.
Daniel is a Research Economist (Fellow) at IES. His main research interests include unemployment and welfare, low pay, and skill demand and utilisation. Since joining IES in September 2021, he has worked across a wide range of public policy and consultancy projects. He regularly works with and analyses labour market data, including the LFS and online vacancy data. Projects he has worked on include the impact and economic evaluations of a government-funded trial of employment support aimed at individuals with disabilities and long-term health conditions, and analysis of the potential of quality part-time employment to lift certain groups out of poverty.
Naomi is a research assistant at the MRC/CSO Social and Public Health Sciences Unit at the University of Glasgow. My research focuses on health inequalities in Scotland and the UK, with a focus on the impacts of accumulated and intersecting experiences of disadvantage for child and adolescent health. This research has utilised several datasets in the UK data service archives, including Understanding Society and the birth cohorts. I am particularly interested in participatory methods and how to co-produce resources for research impact with stakeholders, and am looking forward to exploring these methods further during the fellowship.
Natasha is a third-year PhD student at the Institute of Psychiatry, Psychology & Neuroscience, King’s College London. Her mixed-methods research, which is funded by the ESRC LISS-DTP and in collaboration with Rethink Mental Illness, aims to improve our understanding of multimorbidity for people who have previously experienced homelessness. This is important to inform integrated mental health, physical health, and substance use support for people who have experienced homelessness. Her research includes analysis of the Adult Psychiatric Morbidity Surveys, and interviews with people with lived experience of homelessness and third-sector staff members. Her background is in mental health crisis services and innovative research methods. She is looking forward to sharing more about her research in the coming months as a UK Data Service Data Impact Fellow.
Niels is a Research Fellow at the Violence and Society Centre at City, University of London. Niels investigates violence and abuse and its relationship with labour market transitions, health, and wellbeing and works on a programme of work harmonizing and integrating data from various surveys and administrative records. In much of his previous work, Niels analysed how economic inequalities within and between couples are related to relationship outcomes, such as partner relationship quality, marriage, separation, and childbearing. Prior to joining City, Niels completed his PhD in Sociology at Radboud University in the Netherlands and worked as a researcher at the University of Southampton and University of Bath.
Niloofar is an MRC Early Career Research Fellow at the Centre for Environment and Health, Imperial College London. She uses advanced quantitative techniques to analyse population data in conjunction with a host of environmental and sociodemographic factors, aiming at conducting impactful research that provides valuable insights for equitable policy making. Her current work relates to exploring the role of neighbourhoods in shaping children and young people’s physical and mental health, with a particular focus on the impact of deprivation.
Rhiannon is a PhD student researching housing insecurity at the University of Sheffield as part of the Data Analytics and Society CDT. Her research explores housing insecurity in the UK in relation to changes in welfare policy, with a particular focus on the association between Universal Credit and housing. She uses quantitative data analysis methods, including logistic regression and multilevel modelling.
Tasos is a Research Fellow at the Institute of Public Health and Wellbeing, at the University of Essex. He has a background as a medical doctor, biomedical engineer and computer scientist, with expertise in biosignal and health-related data analysis. His research is in the area of Health Informatics, i.e. the application of machine learning and artificial intelligence methods to problems in clinical medicine and public health. His particular interests include data analysis from biological signals and digitised health data in clinical settings; explainability and appropriate validation in medical image analysis; AI or tech-oriented public health interventions; and the use and benefits of free and open-source software in medicine.