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 Hector Institute of Education Sciences and Psychology at the University of Tübingen in Germany. I am researching how big data can be leveraged to better understand educational attainment and individual differences in learning. Previous work uses machine learning and AI to help prevent modern 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. Recent research is on detecting individual differences in digital traces of behaviour in online learning environments.
BIG DATA PSYCHOLOGY
2015 - 2019
My PhD Investigated 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 - 2021
At the Alan Turing Institute was leveraging big data, machine learning 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
BIG DATA PSYCHOLOGY
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
DATA SCIENCE FOR SOCIAL GOOD
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.
PUBLICATIONS AND PROFESSIONAL ACHIEVEMENTS
Lavelle-Hill, R., Harvey, J., Smith, G., Mazumder, A. & Goulding, J. (2022). Using mobile money data and call detail records to explore the risks of urban migration in Tanzania. In press.
Lavelle-Hill, R. & Mazumder, A. (2022). AI for Detecting Sexual Exploitation Online in the UK: A Review of Indicators and Ethics. In press.
Lavelle-Hill, R., Smith, G., Mazumder, A., Landman, T., Goulding, J. (2021) Machine learning methods for “wicked” problems: exploring the complex drivers of modern slavery. Nature Humanities and Social Science Communications 8, 274.
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.
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"
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"
Awarded The University of Nottingham Travel Prize 2019.
Awarded scholarship by The European Conference of Personality 2018
Interviewed on NottsTV about research on the predictors of plastic bag purchasing. Jan 2022. See news coverage from the Daily Mail.
Interviewed on BBC world service Newsroom on the psychological and demographic predictors of buying plastic bags. Oct 2020.
Speaker at DSSG Data Fest 2019
UNIVERSITY OF NOTTINGHAM
2015 - 2020
PhD in "Big Data Psychology" with
N/LAB, Business School and the School of Psychology
UNIVERSITY OF NOTTINGHAM
2011 - 2015
1st class (HONS) in BSc Psychology (with international study)
Incl. Cognitive Psychology,
Personality and Individual Differences
2013 - 2014
Cultural Perspectives on Health,
Violence Gender and Culture,
Politics in The Middle East,
History of the Holocaust