The use of data to support social decision-making requires a philosophical, methodological and ethical foundation.
We are interested in questions relating to the mathematical foundations of data science, with particular focus on the social context of data science research, including the ethical implications of methodological choices.
Current DSI activity
Kostas Kalogeropoulos
Associate Professor - Department of Statistics
I am involved in two projects on factor analysis, one focusing on model assessment and the other on sequential learning thereof. Another project is on estimating causal effects using Gaussian processes.
Dr Joshua Loftus
Assistant Professor - Department of Statistics
I am interested in statistical and mathematical theory to support applications in the regulation, explanation, and control of machine learning and AI systems, especially in order to reduce social or environmental harms of the proliferation of such systems.
Disaggregated Interventions to Reduce Inequality (2021)
Xinghao Qiao
Assistant Professor - Department of Statistics
Research interests: functional data analysis, high dimensional statistics, time series analysis, Bayesian nonparametrics.
Dr Chengchun Shi
Assistant Professor - Department of Statistics
My research lies in reinforcement learning and analysis of complex data, with applications to healthcare, ridesharing and neuroimaging.
Are you working on this topic? See your research published here by submitting an application to become a DSI Affiliate or to join our Visiting Appointment Scheme.
All applications are welcomed to these schemes that allow staff from across LSE and from other institutions to benefit from special access to DSI resources. Find out more here or via email.
Related LSE research
The strong research community at the London School of Economics also takes an interest in this research theme. As the cornerstone of data science at LSE, the DSI acts as a nexus for research and learning, working alongside other Departments and Institutes across the School.
The Department of Statistics focuses its research activities in the data science area in the area of developing machine learning and statistical methods, their theoretical foundations, and applications.
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