Integration of Models and Data for Inference about Humans and Machines

To bridge the verification and explainability gap of data-driven approaches: We will investigate statistical, mathematical and computational tools that capture realistic prior knowledge about the underlying physical and social process in intelligent behavior to alleviate the burden of training data in learning, underwrite guarantees about system performance, or constrain inference in real time.