Technik- und Ingenieurwissenschaften
Gesina Schwalbe completed her studies of mathematics at the University of Regensburg in 2018. Since then she is a PhD student working at Continental AG on the topic verification of deep neural networks (DNNs) for perception in automated driving. This is supervised by Professor Ute Schmid, head of the Cognitive Systems Laboratory at the University of Bamberg. Gesina's research interests are dedicated to the safety of future autonomous mobility solutions that use DNNs for perception and planning. This encompasses the structure of the safety argument for automated driving perception, and the verification of the internal representation of DNNs with respect to pre-defined symbolic constraints. For the latter she currently investigates in the application of concept activation vectors to semi-formal verification of object detection. This work is part of the German publicly funded project KI-Absicherung aiming for a prototypical safety argumentation of pedestrian detection realized with a deep neural network.
Fragestellungen im Themenfeld Künstliche Intelligenz
Gesina Schwalbe is generally interested in the challenge of safety assurance for deep convolutional neural networks in perception applications. This includes both the safety argumentation structure and methods to provide evidence for the safety argument.
Her main research question is how to enable formal or semi-formal verification of symbolic requirements on convolutional deep neural networks. This combines questions of explainable AI (How to link symbolic concepts with intermediate outputs of a DNN?) and formal verification (How to do this quantitatively? How to formulate verifiable rules on the symbolic concepts?).