Nigel Davies

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.

Chris Nemeth

Chris is a Professor at the School of Mathematical Sciences and joined the Leadership team in January 2024 as the DSI Lead in AI, he became the interim co-director in April 2024. He is Lancaster's Academic Liaison to the Turing University Network and the N8CIR Machine Learning Theme Lead. Chris's main research interests are at the intersection of probability, statistics and machine learning, with a focus on developing the underpinning mathematical foundations of probabilistic machine learning algorithms. In 2018, he was awarded an EPSRC fellowship on Scalable Data Science, and in 2021, an EPSRC Turing AI fellowship on Probabilistic Algorithms for Scalable and Computable Approaches to Learning (PASCAL). He is currently an investigator on the EPSRC-funded Probabilistic AI Hub, and since joining Lancaster, he has been a PI/CI on over £14m worth grant funding.

Sally Keith

In June 2024 Sally became the Environment Theme lead. She is a Senior Lecturer in Marine Ecology within Lancaster Environment Centre, specialising in coral reefs as a model system with which to understand ecological dynamics. She tries to figure out why species are where they are, how they co-exist, and what might happen to these ecological patterns in the future. To do that, she combines fieldwork, statistics, and theoretical modelling to link ecological processes across spatial and temporal scales. In recent years, Sally has become particularly fascinated by the role for animal behaviour in generating and maintaining ecological dynamics at larger spatial scales, recently developing the new field of Macro-behaviour. This research comes with many challenges echoed throughout ecology and many other areas of environmental science, around how to mobilise, quantify, scale up, visualise and interpret data. These challenges can be tackled most effectively by collaboration across data science specialisms, harnessing the power of tools such as AI, VR, photogrammetry and machine learning to enhance fundamental understanding and generate innovative solutions to the biodiversity crisis. You can find out more by visiting Sally's website.

Elisa Rubegni

Elisa joined DSI in September 2024 as an interim Society Theme Lead. Her research lies within the field of Human-Computer Interaction (HCI). She explores the socio-technical issues emerging from the use of interactive technology with the aim of understanding the complex interplay of artefacts, human mind, body, and environment. To meet this complexity, her approach is to combine psychology theories, social science methods and design practice, concretized in developing digital artefacts. Her research is grounded on cultural psychology. and she investigate these issues by recognizing that a successful system can only be developed by fully understanding the fundamental role played by social interactions in the development of cognition, and in the process of "meaning making". Indeed, her research relies on an ecological approach valuing participatory design methods, qualitative and ethnographically informed investigations. She has explored these issues in a broad range of application areas and technologies (e.g. embedded and distributed systems in museums, tangible and gesture user interface in public spaces, large pervasive displays for communities and mobile technology for learning).

Bran Knowles

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.

Bran is on sabbatical in 2024/2025

Chris Edwards

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 Mathematical Sciences, 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 Jewell

Chris is a Professor in Mathematical Sciences, 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

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 Kirkbride

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.