Professor of Consumer Behaviour at Nottingham University Business School, Andrew has extensive expertise in consumer behaviour theory, the analysis of consumption patterns and application of novel time series analysis to consumer purchase data. He has published widely in the fields of: consumer behaviour and psychology; customer loyalty schemes; complexity and consumption; and consumer privacy.
Prior to N-LAB James led the Data Science programme at the RCUK funded Horizon Institute. His core research is in the rapidly growing field of Machine learning with Big Data for social good, focusing on information theoretic techniques to analyse large-scale human behavioural data. He has won an ACM Engelbart prize for work in data theory, a Centre for DE prize for data visualization and also runs the NHS Data Science programme.
Gavin specializes in temporal data mining and machine learning, focusing on development of novel data driven approaches to predict human behaviour in time series. He also researches how to ensure that techniques are applicable in real world scenarios, producing interpretable results. Past work includes theoretical analysis of the limits of predictability in human movement, optimizing symbolisation techniques in time series and dynamic topic modelling (customer mission analysis) in transactional data
John is an Assistant Professor in Marketing at Nottingham University Business School and is the Social Analytics Lead within the Neo-demographic Laboratory for Analytics in Business. He holds a PhD in Economic Anthropology and specialises in the study of informal economies, particularly through ethnographic and computational social network analysis methods. His most recent work examines how data analytics can be applied to the social good of eliminating food waste and food poverty.
Bertrand specializes in Geospatial methods, with a specific focus on mapping in emerging economies and markets – considering how data science methods must be adapted for those regions. He is an expert in geospatial analytics, computer vision and applied machine learning. In addition he is an assistant professor at NUBS, his applied work has covered everything from road condition analysis to detection of slavery from space.
Dr Georgiana Nica-Avram
georgiana.nica-avram@nottingham.ac.uk
Transitional Assistant Professor
Georgiana’s background is in social marketing and consumer behaviour, and she is develops new methods to combine machine learning with qualitative research to better understand the people behind Big Data (via notions of contextualisation, consilience and ethics), with a particular focus on Food Poverty and Waste.
Researchers
Harry’s research examines the potential of applied machine learning to social issues, ranging from ecology to vulnerability. He is part of the UKRI CIVIC project, examining the potential of mass behavioural datasets to reveal hidden insights about unrecorded COVID cases, predictors of potential outbreaks and impacts on vulnerable communities.
Harry.Marshall@nottingham.ac.uk
Gregor’s research examines how mining CDR data can generate Social Good in areas of mobility mapping and urban planning. A specialist in international development analytics, Gregor is currently working on the AIDA project, examining child development in Malawi.
psxge@nottingham.ac.uk
Rosa’s research integrates psychological theory and machine learning to better understand and predict behaviour in big data. Rosa is current a Fellow at the Turing Institute, working on quantative analysis of the drivers of modern slavery both at neighbourhood levels (Tanzania) and at national scales (GSI).
rosa.lavelle-hill@nottingham.ac.uk
Assistant professor in Statistics, at the school of Mathematical Sciences, Katie is also a fellow on the BEADS programme, researching gender equality issues in East Africa, with a focus on perinatal mortality and functional data analysis.
Katie.Severn@nottingham.ac.uk
Rachel has a PhD in statistics, and works on new methods (AJIVE) fusing data streams such as earth observation imagery with survey and CDT data. She is part of the BEADS programme, and EPSRC project examining Gender Inequality in East Africa .
rachel.carrington@nottingham.ac.uk
Madeleine’s work combines the fields of mathematics and international development, examining how block-structure models can be extended to produce social good.
madeleine.ellis@nottingham.ac.uk
Vanja worked as a Senior Analyst before starting her multidisciplinary PhD about behavioural change and perceptions. She explores how people’s beliefs impact their behaviour by combining psychology theories and machine learning techniques.
vanja.ljevar1@nottingham.ac.uk
Elizabeth’s research is developing a framework for “Personal Data Donation”, specifically asking: how can personal transactional data be collected and analysed for the purposes of health research in a way that is acceptable to society, works for infectious and chronic disease, and can be successfully implemented in a clinical setting?
elizabeth.dolan@nottingham.ac.uk
Roberto has an MSc in Analytics, and is researching how consumer loyalty card data can shed light on nutrition and health trajectories, while exploring new methods in variable importance (e.g. model class reliance)
Roberto.Mansilla@nottingham.ac.uk
Bethany is researching the impact of educational interventions in developing contexts, currently looking at methods to analyse X-Prize data from villages in Northern Tanzania. She is jointly supervised by Psychology, as part of the ESRC Midlands Graduate School Doctoral Training Programme
bethany.huntington@nottingham.ac.uk
Dominic is exploring new data science methods to detect those at risk of social isolation. His PhD is in partnership with Ordnance Survey, and is investigating the interrelationship between the factors underpinning isolation and loneliness that might be revealed in digital data streams, from transport and mobility to social media usage.
Dominic.Reedman-Flint@nottingham.ac.uk
Paul is working with N/LAB via the MOCHA project at the University of Cardiff (Lorraine Whitmarsh), examining how pro-environmental lifestyle changes might be achieved through understanding and harnessing ‘moments of change’ in life circumstances, examined through a lens of behavioural datasets, such as loyalty card data.
Paul Haggar
There remains urgent need in the UK to improve understanding of: unrecorded cases of COVID-19; behavioural antecedents to outbreaks; and the hidden impacts to vulnerable communities – the CIVIC project explores these via key indicators logged by health retailers, supermarkets and public services in loyalty card data.
Dominic.Reedman-Flint@nottingham.ac.uk