About me

I am a researcher with a PhD in `Big Data Psychology' combining psychological theory and machine learning to understand human behaviour, with applications in social good domains. I am currently working at The Alan Turing Institute (the UK's National Institute of Data Science and AI) using machine learning, artificial intelligence, and bayesian statistics to help prevent modern day slavery and human trafficking.



March 2017 - Present

Analysing academic datasets on student performance using machine learning methods with the goal of understanding bias in the data, and develop fair and accurate marking methods across a range of subjects and departments.


October 2015 - Present

Investigating how psychological research is best conducted using big data, where the goals are to have interpretable and generalisable models of human behaviour. In collaboration with the School of Psychology and N/LAB at The University of Nottingham.


October 2019 - Present

At the Alan Turing Institute I am using machine learning, bayesian methods, and AI to better measure, understand, and ultimately help prevent modern slavery, human trafficking, and other exploitative crimes.


July 2013 - August 2013



During the 6 week Developmental Psychology internship at The University of Nottingham I actively helped to plan and run the university's Summer Scientist Week (SSW). SSW is a fun few days for children, which also serves as a pool of participants for the Developmental Psychology researchers working in and around Nottingham. My role involved event organisation, setting up the data base, testing the children's vocabulary ability using BPVS (including autistic children), calibrating the test scores, and inputting and analyzing the data in Excel.

July 2015 - October 2015


A lot of our daily purchases are driven by various psychological factors. For example, people can buy chocolates either because of habit or because of lapses in self-control when facing a pack of Maltesers at the till. Whilst a wealth of decision-making literature studied psychological mechanisms of impulsive and habitual behaviours in the lab, there is still not enough research translating decision-making theories into real world choices. The Digital Economy opens up a new era in the research of human behaviour, as information about what we buy, where we travel and even what we eat can be recorded “online”, producing evidence that is more accurate than self-reported logs. This project analysed how we categorize and understand different clusters of individual daily decisions and how to interpret the outputs of these analyses.

June 2019 - August 2019



I was a fellow on the Data Science for Social Good (DSSG) 2019 ran by Imperial College London and in partnership with The University of Chicago, The Alan Turing Institute, and Warwick University. This programme looks at how we can harness the power of data science to enable charities, start-ups, NGOs and governmental departments operating in the social good space to grow. I worked on a project in partnership with IEFP in Portugal, building a recommender system to improve employment outcomes in mainland Portugal.


Journal Publications:

Lavelle-Hill, R. et al. (2021). Machine Learning Methods for "Small-n, Large-p" Problems: Understanding the Complex Drivers of Modern-Day Slavery, PREPRINT available at Research Square 

Lavelle-Hill, R., Goulding, J., Smith, G., Clarke, D. D., & Bibby, P. A. (2020). Psychological and demographic predictors of plastic bag consumption in transaction data. Journal of Environmental Psychology, 72, 101473.

Lavelle-Hill, R. E., Skatova, A., Goulding, J., Bibby, P., & Clarke, D. (2020). Buying what people like you buy: Personality Homophily and Well-being in Consumer Behaviour. PREPRINT available at OSF

Tomas, C., Whitt, E., Lavelle-Hill, R., & Severn, K. (2019). Modelling holistic marks with analytic rubrics. In Frontiers in Education (Vol. 4, p. 89). Frontiers.


Data for Policy 2020, London (virtual). "Using machine learning methods to better understand the complexities of modern slavery" 

UCL LIDo PhD Programme, London  2020. "Big Data Psychology"

DSSG Data Fest, Imperial College London 2019. "Building a Recommender System to Improve Employment Outcomes in Portugal"

World Conference of Personality, Hanoi 2019. "Bags of money or bags of Impulsiveness? Psychological and Demographic Predictors of Plastic Bag Consumption in Big Data."

European Conference of Personality, Zadar 2018. "Using Machine Learning Techniques to Examine the Relationship between Money, Personality, and Well-being."

GovTechLab Knowledge Transfer Consortium, London, 2018. "Big Data for Social Good"

Other achievements:

Awarded The University of Nottingham Travel Prize 2019.

Awarded scholarship by The European Conference of Personality 2018

Media Engagements:

Turing blog post. "Black Friday 2020 survival guide: Will recession or AI save us from impulse buying this year?"

Interviewed on BBC world service Newsroom on the psychological and demographic predictors of plastic bags. Oct 2020.

Speaker at DSSG Data Fest 2019



2015 - 2020

PhD in "Big Data Psychology" with

N/LAB, Business School and the School of Psychology


2011 - 2015

1st class (HONS) in BSc Psychology (with international study)
Incl. Cognitive Psychology,
Biological Psychology,
Developmental Psychology,
Personality and Individual Differences


2013 - 2014

Swedish Language,
Cultural Perspectives on Health,
Scandinavian History,
Evolutionary Psychology,
Violence Gender and Culture, 
Politics in The Middle East,
History of the Holocaust


Data Fest 2020 poster
Data Fest 2020 poster
World Personality Conference 2018
World Personality Conference 2018
DSSG 2019
DSSG 2019
Data Fest 2019
Data Fest 2019
DSSG Project Team
DSSG Project Team
Data Fest 2019
Data Fest 2019
Data Fest 2019
Data Fest 2019
Data Fest 2019
Data Fest 2019
DSSG 2019
DSSG 2019