Niklas Pfister, assistant professor
Niklas has been employed as a tenure track assistant professor at the section for Statistics and Probability Theory in the Department of Mathematical Sciences.
As part of the Copenhagen Causality Lab (CoCaLab), Niklas will continue and extend his work on causal inference and investigate how these techniques can be combined with modern machine learning methods.
In 2019, Niklas completed his PhD entitled “Intervention stability in statistics: Benefiting from causality” at ETH in Zürich, Switzerland. His research has involved developing statistical methodology for problems motivated by the applied sciences, with a particular focus on biological applications.
His work includes methods for mutual independence testing, adjusting independent component analysis (ICA) for unobserved confounding and techniques for causal inference based on the principle of invariance for sequential data and dynamical systems.
Feel free to drop by his office (04.1.18) or send him an email (email@example.com). He is always happy to hear about challenging statistical problems you have come across.