The problems studied in the department can be subsumed under the heading of empirical inference, i.e., inference performed on the basis of empirical data. This includes inductive learning (estimation of models such as functional dependencies that generalize to novel data sampled from the same underlying distribution), or the inference of causal structures from statistical data (leading to models that provide insight into the underlying mechanisms, and make predictions about the effect of interventions). Likewise, the type of empirical data can vary, ranging from biomedical measurements to astronomical observations. Our department is conducting theoretical, algorithmic, and experimental studies to advance study of empirical inference.