I develop new psychophysical methods to perform robust experiments, e.g. novel experiments to objectively quantify causal perception and apply the theory of causal inference to questions in cognitive science. My current focus is on the perception of the direction of causal flow. I study whether humans and machines are able to perceive temporal causal relationships between objects. I published a NeurIPS and an i-perception paper on this topic.

Recently, I also got interested in the comparison of Neural Network and humans and the underlying causal mechanism. Humans and Deep Convolutional Neural Networks (CNNs) show surprisingly similar performance in many tasks. But does it mean that they use the same underlying mechanism? We are currently developing new methods for the comparison of strategies.

Finally, I am not only working on my PhD but I am also studying law. I think there are many areas where I can bring together legal knowledge and computer science. My particular interest lies in all issues surrounding IT and law: data privacy, IT-security and machine learning. Currently, I am working on problems related to the GDPR and modern machine learning algorithms.