Daniel Stahl is a Professor of Medical Statistics and Statistical Learning and lead of the Precision Medicine and Statistical Learning Group.
Daniel started his academic career as a behavioural biologist at the German Primate Center in Germany. During his PhD, Daniel became aware of the importance of statistics and data science. He attended an MSc in Biostatistics and has worked since then as a statistician in academic research institutions in Germany, Scotland and – since 2006 – at King’s College in London. He is now lead of the “Precision Medicine and Statistical Learning Group”. A primary focus of the group is to develop tools to aid clinical decision using predictors which can be easily, reliably and cost-effectively collected from mental health service users.
Daniel’s interest is applying statistical and machine learning methods to identify predictors, mediators, and moderators of treatment success and using model-based cluster analysis methods to identify subgroups among psychiatric patients. His methodological research concerns the correct treatment of missing data in machine learning procedures and the assessment of subgrouping in prediction modelling.
As a Lead Trial Statistician, he has been responsible for overseeing the statistical aspects of a number of clinical trials within the IoPPN. Daniel is also interested in model selection problem, improving the low reproducibility of medical studies and- a blast from my past – in the evolution of social system in primates.