Oisín Ryan is an Assistant Professor in the Real World Evidence group at the Department of Data Science and Biostatistics. He is the coördinator of the summer school Introduction to Causal Inference and Causal Data Science.

 

Oisín’s research focuses on developing approaches and tools to help researchers study causal relations using observational data. In the Real World Evidence group he co-ordinates a team of statisticians and causal inference experts, who apply and research causal inference methods for population-scale health registry data, often in regulatory settings concerning the safety and efficacy of medicines and vaccines. He co-ordinates the Special Interest Group in Causal Data Science at UU/UMCU. Prior to joining the UMCU he completed a research masters and PhD in the Department of Methodology and Statistics at UU, where he developed masters-level and summer school courses in time-series analysis and causal inference.