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Dr James Goulding

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Dr James Goulding

B34c North Building, University of Nottingham, NG8 1BB


About James

James Goulding is co-director of N/LAB, a centre of excellence in international analytics at the University of Nottingham (see; He lectures in data science, and business analytics and his background is uniquely multidisciplinary with a BSc in Economics, an MA in Management of IT, and a PhD in Machine Learning. He has extensive expertise in the development of novel techniques to analyse large-scale human behavio ural data; research focuses on bridging the gap between behavioural science and recent advances in AI and Machine Learning, particularly to achieve sustainable development goals.


James is highly research active, with with >70 international peer-reviewed publications crossing disciplines of social and computer science, winner of ACM Engelbart prize for data theory and Centre for DE prize for data visualisation. Since 2017, he has expanded the N/LAB research centre from its initial 3 members to over 20 research fellows, PhDs and academic staff.




With a proven grant record, and being PI/CO-I on Research programmes of over £15m since 2015 (EPSRC, ESRC, Gates, British Council, Newton) he is an accomplished coordinator of large, international research projects, with rich experience of bringing research to real world impact in applications of sustainability. This research has used novel Big Data streams (mass retail data, telco logs, mobility data) to reveal key behaviours/ drivers underpinning UN SDGs. (Sustainable Development Goals). Work has advanced knowledge in behavioural factors contributing to: food waste (UK/Innovate UK), mental health (UK/EPSRC), Perinatal Mortality (Zanzibar/DfID); Dengue Fever transmission (Malaysia/British Council); Domestic Servitude and Gender Inequality (North India/Arise); Educational Development Challenges (Malawi/ESRC); and factors perpetuating poverty in in East Africa (Tanzania/EPSRC). A founding committee member of UN’s Code 8.7 initiative to use AI to end modern slavery, and lead for NHS’s data science program.


In order to establish N/LAB as a permanent centre, James also build strong data-sharing partnerships with a wide array of businesses, including: Walgreen Boots Alliance, Marks & Spencer, 7-eleven (China), TiGo (Tanzania), Ipsos Mori, Experian and the NHS. This has resulted in production of a research dataset covering the behaviour of around 100 million people across the world, and a growing body of multi-institutional projects. James also has extensive lecturing experience (successfully convening 9 different UoN modules), won the 2018 MSc teaching award, and has supervised 15 PhDs (9 to completion as of writing) plus over 100 Masters Dissertation projects.



Reseach areas

Behavioural Analytics, Machine Learning, Time Series Prediction, International Development, Consumer Psychology, Econometrics.

James is currently collaborating on the following projects:

  • CDT in Geospatial Systems (led by Newcastle)
  • Horizon: Trusted Data Driven Products

Recent Publications

Journal article 2022 R. Lavelle-Hill, J. Harvey, G. Smith, A. Mazumder, M. Ellis, K. Mwantimwa, J. Goulding, (2022), “Using mobile money data and call detail records to explore the risks of urban migration in Tanzania”, , Vol.11(28).

Journal article 2021 Lucas, B.; Francu, R.E.; Goulding, J.; Harvey, J.; Nica-Avram, G.; Perrat, B. (2021), “A Note on Data-driven Actor-differentiation and SDGs 2 and 12: Insights from a Food-sharing App”, Research Policy, Vol.50, 1042662.

Journal article 2021 Nica-Avram, G; Harvey, J.; Smith, G.; Smith, A.; Goulding, J. (2021), “Identifying Food Insecurity in Food Sharing Networks via Machine Learning”, Journal of Business Research, Vol.131, 469-484.

Journal article 2021 Rosa Lavelle-Hill, Gavin Smith, Anjali Mazumder, Todd Landman & James Goulding, (2021), “Machine learning methods for “wicked” problems: exploring the complex drivers of modern slavery”, Humanities and Social Sciences Communications.

Journal article 2020 Gavin Smith, James Goulding, Roberto Mansilla, (2020), “Model Class Reliance for Random Forests”, Advances in Neural Information Processing System, Vol.34.

Journal article 2020 Harvey, J.; Smith, A; Golightly, D.; Goulding, J.; Gallage, H.P.S. (2020), “Prosocial Exchange Systems: Nonreciprocal giving, lending, and skill-sharing”, Computers in Human Behavior, Vol.107, 106268.

Journal article 2020 Nica-Avram, G.; Goulding, J.; Harvey, J. (2020), “FIMS: Identifying, predicting and visualising food insecurity”, World Wide Web: Internet and Web Information Systems, 190-193.

Journal article 2020 Rosa Lavelle-Hill; James Goulding; Gavin Smith; David D. Clarke; Peter A. Bibby, (2020), “Psychological and demographic predictors of plastic bag consumption in transaction data”, Journal of Environmental Psychology, Vol.72, 101473.

Journal article 2020 Smith, Andrew; Harvey, John; Goulding, James; Smith, Gavin; Sparks, Leigh, (2020), “Exogenous cognition and cognitive state theory: the plexus of consumer analytics and decision-making”, Marketing Theory, 1.47059312096495E+15.

Journal article 2019 Harvey, J., Smith, A., Goulding, J., Branco-Illodo, I. (2019), “Food Sharing, Redistribution, and Waste Reduction via Mobile Applications: A Social Network Analysis”, Industrial Marketing Management.

Journal article 2019 James Goulding; Anya Skatova, (2019), “Psychology of Peronsal Data Donation”, PLoS One, Vol.14/11, e0224240.

Journal article 2017 Brindley, P., Goulding, J., Wilson, M.,, (2017), “Generating Vague Neighbourhoods through Data Mining of Passive Web data”, International Journal of Geographical Information Science: IJGIS, Vol.32 (3), pp. 498-523.

Journal article 2017 Dzogang, F.; Goulding, J.; Lightman, S.; Christianini N;, (2017), “Seasonal Variation in Collective Mood via Twitter Content and Medical Purchases”, Lecture Notes in Computer Science (LNCS), Vol.10584, pp. 63-74.

Journal article 2015 Liu, H., Goulding, J., Brailsford, T. (2015), “Towards Computation of Novel Ideas from Corpora of Scientific Text”, Lecture Notes in Computer Science (LNCS), Vol.9285, pp. 541-556.

Report for external body 2020 Rights Lab, 2020, “Beyond the walls: Microdata on domestic workers in north east India”, in, Rights Lab.

Conference Contribution/ Proceedings 2021 V. Ljevar, J. Goulding, G Smith, A. Spence, 2021, 2021, “Using Model Class Reliance to Measure Group Effects on Non-Adherence to Asthma Medication”, in IEEE International Conference on Big Data, IEEE.

Conference Contribution/ Proceedings 2020 Seymour, R.; Goulding, J.; Preston, S.; Sirl, D. 2020, “Bayesian Nonparametric Methods for Comparative Judgement Models and Vulnerability Estimation in Developing Countries”, in International Symposium on Nonparametric Statistics.

Conference Contribution/ Proceedings 2020 Smith, G.; Mansilla, R.; Goulding, J. 2020, “Model Class Reliance for Random Forests”, in 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada., NeurIPS.

Conference Contribution/ Proceedings 2019 Goulding, J.; Harvey, J.; Smith, A. 2019, “An exploratory network analysis of balance, reciprocity, and assortativity in a P2P food sharing network”, in NETSCIX.

Conference Contribution/ Proceedings 2019 Smith, A; Harvey, J; Goulding J, Smith G, 2019, “Consumer analytics, exogenous cognition and the disciplinary nexus.”, in 8th M-Sphere Conference for Multidisciplinarity in Business and Science, Dubrovnik Croatia, October 2019.

Conference Contribution/ Proceedings 2018 Gregor Engelmann, Gavin Smith, James Goulding, 2018, “The Unbanked and Poverty:Predicting area-level socio-economic vulnerability from M-Money transactions”, in Proceedings of IEEE Big Data (journal equivalent), IEEE, pp. 1357-1366.

Conference Contribution/ Proceedings 2017 Avram, G., Goulding, J., Cluley, R. 2017, “Outdoor Advertising and Daily Journeys to School”, in World Social Media Conference, 2017, Washington DC..

Conference Contribution/ Proceedings 2017 Avram, G; Goulding, J; Smith A. 2017, “Creatures of habit and Creatures of Context: Mining Customer Similarity Based on Recurring Shopping Behaviours via Non-Negative Matrix Factorisation”, in American Marketing Association Winter Conference. Orlando, FL. USA.

Conference Contribution/ Proceedings 2017 Darler, W; Goulding, J; Smith, A; Roberts, D, 2017, “A Framework to Segment Life Events Using Customer Transaction Data”, in Winter AMA Conference, Orlando, Florida.

Conference Contribution/ Proceedings 2017 Engelmann, G., Goulding, J., and Golightly, D. 2017, “Estimating activity-based land-use through unsupervised learning from mobile phone event series in emerging economies”, in GISRUK.

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