Bio
Ognyan Simeonov (Ogy) is a PhD student at the University of Edinburgh. He is part of the Artificial Intelligence Applications Institute at the School of Informatics and the MAC-MIGS CDT program led by the University of Edinburgh (UoE) and Heriot Watt University. Ogy completed his Bachelor of Science in mathematics and economics at Bates College, ME, USA in 2022 and moved to the UK to join the MAC-MIGS doctoral program in the same year. He is currently supervised by Dr. Valerio Restocchi and Dr. Ben Goddard. His current research focuses on applying network science methods on socio-economic systems in order to understand consumer spending patterns. He studies the impact of sustainable fintech on spending behaviour and analyses the carbon emissions of environmentally conscious groups of individuals compared to the general population. He believes that understanding the environmental impact of spending on household and individual level can help us reach carbon neutrality faster. Ogy is passionate about developing and applying human behaviour models for a more sustainable future. He is also interested in the ethical implications of his research, and would be happy to collaborate with other researchers working with large financial/bank datasets to understand the role of human behaviour on spending and sustainability.
Research interests
Ogy works on analysing large debit card transaction datasets using network science tools. He aims to understand consumer purchasing patterns and develop behavioural nudges that will encourage customers to reduce their carbon emissions by changing their spending habits. He applies a variety of network science and data analysis techniques, such as network motif analysis, to draw connections between different socio-economic indicators and the carbon emissions associated with customers. He uses various UK government datasets (e.g. the Living Cost and Expenditure Surveys and the Index of Multiple Deprivation datasets) to compare the spending and carbon emissions estimated through transaction datasets to overall consumer expenditure. He also identifies key categories of goods and services that are associated with high carbon emissions and the profile of the customers with high spending in these categories. This research would allow him to construct refined incentives for different socio-economic groups of customers that will be applied on the customer base of a debit card company. This project has the potential to be an essential part of the decarbonisation process of the UK economy and help the AI for decarbonisation incentives of the Turing Institute.