Dr. Melanie Schaller completed her PhD at the university of Würzburg in 2023 focusing on the application of Cyber-Physical Systems for non-invasive monitoring of intracranial pressure via a pressure derivative. On the software side, she emphasizes integrating engineering knowledge into machine learning models in an end-to-end manner, methods of anomaly detection in multivariate time-series as well as graph signal processing. On the hardware side, her focus lies on sensor network applications.

She has completed several projects in the field of machine learning research. The P-BIM project aimed to distinguish between normal structural swinging behavior and anomalous deformations of structures. Using graph neural networks, the bridge structure was modeled based on sensor network data and used to automatically extract eigenmodes with a novel graph convolutional filter design. In the KI@FlowChief project, the goal was to detect and localize leakages in water distribution networks to reduce water waste. Therefore, she utilized head-loss-based edge weights in a heterogeneous graph neural network.