معرفی
Paul Bürkner is a Full Professor of Computational Statistics at TU Dortmund University, focusing on probabilistic (Bayesian) methods. His research sits at the intersection of statistics and machine learning, with applications across quantitative sciences.
- Key Roles: Developer of the brms R package, member of the Stan and BayesFlow development teams.
- Research Pillars: Bayesian inference, uncertainty quantification, amortized workflows, simulation-based inference, and probabilistic programming.
His lab advances methods for prior specification, model evaluation, and scalable inference, collaborating on applications from cognitive science to ecology. Recent work emphasizes neural superstatistics and BayesFlow for efficient mixture and multilevel models. Students and researchers are encouraged to reach out for collaboration or thesis opportunities.
Key Labs/Teams:
- BayesFlow Development Team
- Stan Project
- ELLIS Network (European Laboratory for Learning and Intelligent Systems)
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