Research
The DSI supports and promotes research by Institute staff, visiting scholars and DSI Faculty and PhD Affiliates that examines the societal impacts of data and AI, leverages emerging technologies to enhance research methodologies, and contributes to the development and refinement of AI capabilities.
AI research at LSE
DSI affiliate networks
DSI Faculty Affiliate Network
Join our network of academics from across LSE who are engaged with data science and AI in their research and teaching.
DSI PhD Affiliate Network
Join our PhD Affiliate Network of PhD researchers working in relation to data science and AI.
Selected research highlights
Research news and events from the DSI
(De)constructing health and wellbeing through data | Impact Wednesdays talk
Professor Elizabeth Stokoe is joined by Dr Alexandra Gomes (LSE Cities) and Jeremy Morley (Ordnance Survey) to discuss their joint research project.
LLM-enhanced research methods for large scale qualitative data | Event recording
This talk addresses the practical and methodological challenges of deploying LLMs as automated 'method execution' assistants, carefully guided and evaluated by human researchers.
Chatbots can influence political views, new study finds
Information-packed arguments were found to be the most convincing but least accurate.
LSE academic appointed to United Nations Panel on AI
Professor Sonia Livingstone has been appointed to the UN’s Independent International Scientific Panel on AI
Research projects
Selected data science and AI research projects and groups
Zambia Evidence Lab
Embedded inside government, the Lab helps shift Zambia’s public sector towards sustained, data-informed decision-making.
GENIAL: GENerative AI Tools as a Catalyst for Learning
A research project exploring how university students use popular GenAI tools in their learning and assessments.
(De)constructing health & wellbeing through data
An analytical project exploring data interdependencies and socio-spatial connections to understand how the physical environment impacts health and wellbeing.
DIVIDED: preventing the polarising effects of economic inequality
DIVIDED explores socio-economic and political divisions, focusing on two defining challenges for modern democracies: rising economic inequality and political polarisation.
Department of Statistics data science research group
This group focuses on developing machine learning techniques and computational methods for statistical analysis.
Improving air quality in cities: forecasting air pollution in Kuwait
This research aims to enhance the accuracy of PM2.5 concentration forecasts in Kuwait by employing advanced deep learning models.
Library services for research data
