Universitetsparken 5, 2100 København Ø, E/04, Building: 04.3.28
My PhD project aims at advancing the field of causal structure learning. Given data from different environments (e.g., different experimental designs, or spatial / temporal domains), the stability of causal dependencies can be exploited to infer (parts of) the underlying (unknown) causal graph. My project is in particular concerned with situations in which relevant parts of the causal system cannot be observed.
Supervisor: Jonas Peters
Primary fields of research
Causal inference, invariance, regression analysis, information theory, hidden Markov models