Roland is a professor of statistics and data analysis at Bielefeld University, Germany, where he is extensively involved in teaching both introductory statistics courses and advanced statistical methods. His research focuses on the development of statistical approaches for state-switching time series models, in particular hidden Markov models (HMMs), and on their applications across ecology, sports, and economics. Within statistical ecology, he has published widely on the modelling of animal movement and behaviour, as well as on capture–recapture and distance sampling methods.
Education & Career
• PhD in Statistics (specialising in hidden Markov models and time series analysis)
• Professor of Statistics and Data Analysis, Bielefeld University
• International collaborations across ecology, sports science, and economics
Research Focus
Roland’s research is centred on both the theoretical and applied development of hidden Markov models and related state-switching time series methods. He is particularly interested in bridging methodological innovation with real-world applications, especially in ecological research on animal movement, capture–recapture, and behavioural analysis. His interdisciplinary work also extends to sports analytics and economic modelling.
Current Projects
• Development of new methods for hidden Markov models and related state-switching models
• Statistical modelling of animal movement and behaviour using biotelemetry data
• Advances in capture–recapture and distance sampling methodology
• Applied collaborations in sports performance analysis and economic time series modelling
Teaching & Skills
• Teaches foundational statistics and advanced statistical methods at Bielefeld University
• Specialist in hidden Markov models, state-switching models, and statistical ecology
• Strong advocate for combining rigorous methodology with applied problem-solving across disciplines
Links
• ResearchGate
• Google Scholar
• University Profile