Universitetsparken 5, 2100 København Ø, E/04, Building: 04.3.28
I am a postdoc in statistics at the University of Copenhagen. In September 2020, I officially obtained my PhD degree based on the thesis “Causal inference in the presence of latent variables: structure learning, effect estimation and distribution generalization”. I guess the title does not leave much to the imagination — I am interested in causality, latent variables models, invariance and transfer of knowledge between data sets (generalization).
I am also very curious about applying causal concepts to real-world problems. Real data often confronts us with unexpected challenges and motivates us to rethink our theoretical concepts. For example, in one of the chapters of my thesis, we discuss the causal relation between armed conflict and tropical forest loss in Colombia, which lead to the development of a new causal framework for spatio-temporal data. Such interdisciplinary projects are exciting and relevant, since they promote methods which are rooted in real scientific questions. So, if you have an interesting data scientific question which requires a causal approach, come talk to me — I am always open to collaborate! I am particularly interested in applications in the natural and social sciences.
Primary fields of research
Causal inference, invariance, regression analysis, latent variable models, distribution generalization, applications in the natural and social sciences