Professor Daniel Stahl

Biography

I studied Biology at the University of Tübingen, Germany and started my academic career as a behavioural biologist at the German Primate Centre Göttingen and Emory University, Atlanta, USA. During my PhD on food competition within primate groups, I became interested in statistics and mathematical modelling and took an MSc equivalent course in Biostatistics and distance courses in mathematics and started my second career as a statistician. As a statistician at the University of St. Andrews, I modelled the distribution of whales in Antarctica and white fish in the North Sea. I then worked as a statistician at the Max-Planck Institute for Evolutionary Anthropology, Leipzig, Germany for the Departments of Primatology and Developmental Psychology.  I joined the King’s College in 2006 as a Lecturer in Biostatistics. Today, I am a Professor of Medical Statistics and Statistical Learning in the Department of Biostatistics and Health Informatics and lead of the "Precision Medicine and Statistical Learning Group". My interest is the application of statistical and machine learning methods to vital mental health research questions in order to develop robust prognostic models and prediction models of treatment response in mental health. I am also interested in process analyses and the interplay between physical and mental health problems. I am also lead statistician in clinical trials. As Education lead, I am responsible for the academic aspect of our education programme, including our newly established Postgraduate Certificate in “Applied Statistical Modelling and Health Informatics” (MSc in 2020). I am the organizer of the annual “Prediction modelling” course and teach introductory and advanced statistics for MSc students at the IoPPN. I am co-author of the book “Cluster analyses” (Wiley 2011)

Research Interests:

• Prediction Modelling
• Statistical/Machine Learning
• Model Selection
• Mediation and Moderation
• Missing Data in Prediction Modelling
• Cluster Analyses

Teaching:

• Prediction Modelling
• Path analyses and Structural Equation modelling and Path analyses
• Machine learning, big data and personalised medicine.

Expertise and Public Engagement:

Public Facebook page and Twitter about prediction Modelling in Psychiatric Research:

• https://www.facebook.com/predpsychUK/
• https://twitter.com/predpsychuk