Nigel Davies is a Distinguished Professor of Computer Science and Co-Director of DSI@Lancaster. He has held visiting positions at Sony Electronics, Google Research, ETH Zurich and CMU. His work is in the area of pervasive computing including systems support for new forms of data capture and interaction and is characterised by an experimental approach involving large-scale deployments of novel systems with end-users. He has chaired many of the major conferences in the field and is a former editor of IEEE Pervasive Computing and an Associate Editor of IEEE Transactions on Mobile Computing. He has been PI or CI on over £9.8 million worth of grants.
Karen Broadhurst is Professor of Social Work in the Department of Sociology and since June 2021 Co-Director of DSI@Lancaster. Karen also co-directs the Centre for Child and Family Justice Research and is establishing the Nuffield Family Justice Observatory. She has a particular interest in the use of large-scale administrative data for social research and is currently leading a programme of work (2018 - 2023) in partnership with colleagues at the SAIL Databank (Swansea University), which aims to build capability in the use of data collected routinely by government and other agencies. Use of population-level data is in its infancy in the field of family justice and this Nuffield initiative, speaks to long-standing concerns about the limited and contested place of social science in family court decision-making.
From June 2021 Amber is on maternity leave and Gordon Blair has re-joined the Leadership Team. In Feb 2020 Amber became the Environment Theme lead. She is a Senior Lecturer in Applied Data Science and is also the co-theme lead for Ice/Water in the new Centre for Excellence in Environmental Data Science (CEEDS) and so is ideally placed to provide synergy between the LEC, DSI and CEEDS communities. Amber’s main research interest is in ice-climate interactions; specifically how climate change affects the Greenland and Antarctic Ice sheets. Her day-to-day work mostly involves developing improved numerical models of the Cryosphere, in order to advance their capability for robust estimates of cryospheric change. This is supported by extensive work with Remote Sensing data and GIS techniques.
Bran joined the leadership team in September 2021. She is a qualitative researcher with a mixed disciplinary background spanning computing, design, sociology, and anthropology. Her work explores ethical considerations surrounding data and data systems, with a particular focus on promoting trustworthy data systems (especially AI/ML). Current work explores strategies for promoting trust in the face of uncertainty inherent in environmental data science, develops a protocol for mitigating bias in algorithmic hiring, and considers how to adapt algorithmic documentation to support regulatory enforcement of trustworthy AI. She is keenly interested in issues of inequality arising from the use of data systems, and recently co-authored a book on the topic entitled "A Watershed Moment for Social Policy and Human Rights?: Where Next for the UK Post-COVID." Other interests include data protection issues and various harms stemming from new uses of children's data, mitigating harms to marginalised groups (particularly older adults), and issues of governance. She is an elected member of the ACM Europe Council and serves on the Executive Committee for the ACM Europe Technology Policy Committee.
Chris Edwards is a Professor of Computer Science, and the Education theme lead of DSI@Lancaster. For the past six years he has been working on improving postgraduate taught education at Lancaster, a significant part of which has been to develop and lead the MSc in Data Science, which first recruited in October 2014. The multidisciplinary programme is run jointly by the departments of Computing and Communications and Mathematics and Statistics, with input for specialisms from the Environment Centre, the Management School, and the Faculties of Health and Medicine, and Arts and Social Sciences. Chris is also the Director of the newly established University Doctoral Academy.
Chris is a Professor in Maths and Stats, and N8CIR Digital Health Theme lead at Lancaster. His interest in high-performance computing and research software engineering comes through designing real-time decision support systems for infectious diseases, applied to outbreaks such as foot and mouth disease and SARS-CoV-2. His research currently uses GPU-accelerated Bayesian learning methodology, using high-level machine learning libraries such as Tensorflow and Theano, as well as direct CUDA implementations. Chris’s role in this group is largely management, though he hopes to contribute research-focused “how-to” sessions as the seminar programme develops.
Heather Brown is a Professor of Health Inequalities and since September 2022 has been Theme Lead for Health in DSI. She leads the Equitable Place Based Health and Care Theme for NIHR ARC North West Coast. Her main research interests are the economics causes and consequences of health inequalities and policy evaluation. She is particularly interested in inequalities across and between generations and how local policies can reduce these inequalities by removing structural barriers. Heather uses large datasets including linked data to evaluate policy as well as identify current trends and areas for future policy and interventions. She is also interested in engaging with a wide range of stakeholders to make complex quantitative data analysis accessible and user friendly.
Chris joined the Leadership team in January 2022. Chris is a Senior Lecturer in the Department of Management Science. His research is concerned with decision making under uncertainty. In such problems actions are taken in response to current information about the environment you are operating in. Chris's primary interest lies in developing novel solutions that describe the ‘best’ action to take in these random environments over time. This involves a range of methodologies from optimization, stochastic dynamic programming, simulation and reinforcement learning.