Graph Representation Learning Reading Group @ Mila - Quebec AI Institute
Description: Full Professor @ University of Cologne
I am a tenured professor for Computer Science at the University of Cologne where I lead the research group on Trustworthy Artificial Intelligence. Broadly speaking my research is about models and algorithms that are not only accurate or efficient, but also robust, uncertainty-aware, privacy-preserving, fair, and interpretable. One focus area of my research is trustworthy graph-based models such as graph neural networks. Previously I was faculty at the CISPA Helmholtz Center for Information Security. Before
We have multiple open positions in our research group on a variety of (trustworthy) machine learning topics.
A cursory reading of the literature suggests that we made a lot of progress in designing effective adversarial defenses for Graph Neural Networks (GNNs). Yet, the standard methodology has a serious flaw – virtually all of the defenses are evaluated against non-adaptive attacks leading to overly optimistic robustness estimates. We perform a thorough robustness analysis of 7 of the most popular defenses spanning the entire spectrum of strategies, i.e. aimed at improving the graph, the architecture, or the tra
Graph Representation Learning Reading Group @ Mila - Quebec AI Institute