The increasing availability of complex data from multiple sources presents both new opportunities and methodological challenges for statistical analysis. This webinar brings together researchers working on the statistical foundations and emerging applications of data integration and data fusion, with a focus on how information from heterogeneous sources can be effectively combined while accounting for uncertainty, dependence, missingness, and potential sources of bias.

Prof Paul Kirk and Prof Shu Yang will discuss recent methodological developments and applications illustrating how statistical modelling can address these challenges in different settings. The talks will highlight the opportunities and challenges associated with combining complementary sources of information, as well as the role of principled statistical modelling in extracting meaningful and reliable insights from integrated data.

The webinar will provide an opportunity to explore common methodological themes across different applications and to discuss emerging directions in statistical data integration and fusion.