Computational Network Science Group

The Computational Network Science group headed by Michael Schaub is part of the Computer Science Department at RWTH Aachen University within the Faculty of Mathematics, Computer Science and Natural Sciences.
The research interests of our group are broad, but have one common denominator: the use of networks to analyse a variety of systems and data. See the Research page for more details, or click on one of the topics below.

Latest news

May 20, 2025

HOOC - Higher Order Opportunities and Challenges

We are happy to announce the HOOC workshop on higher-order networks. Attendance is free! Go to https://conf.netsci.rwth-aachen.de for more information and registration.

Network analysis has revolutionized our understanding of complex systems, and graph-based methods have emerged as powerful tools to process signals on non-Euclidean domains via graph signal processing and graph neural networks. However, graphs are ill-equipped to encode multi-way and higher-order relations – features that are essential to understanding many systems such as group-dynamics in social systems, multi-gene interactions in genetic data, or multi-way drug interactions.

Accordingly, there is a need for new analytical methods to address the challenges of higher-order data, and a growing body of work in this direction. With this workshop, we especially want to explore current challenges which arise when bridging theory and data. This means on the one hand discussing what higher-order methods have already been used with real-world data, and on the other hand, what challenges currently prevent modelling systems with higher-order interactions.

The workshop will take place from the 11th to the 13th of August 2025. We look forward to welcoming you in Aachen, Germany!

May 20, 2025

Paper accepted at EUSIPCO 2025

Our paper "Faster Inference of Cell Complexes from Flows via Matrix Factorization" got accepted at EUSIPCO 2025. In this paper, we consider…
May 16, 2025

Paper accepted at KDD 2025

Our paper "HLSAD: Hodge Laplacian-based Simplicial Anomaly Detection" has beeen accepted at KDD 2025, taking place in Toronto, Canada from…
May 7, 2024

Paper accepted at ICLR 2024

Our paper "Learning From Simplicial Data Based on Random Walks and 1D Convolutions" has been accepted at ICLR 2024. In this paper, we…

Contact

Prof. Michael Schaub, PhD

Ahornstraße 55
52074 Aachen

Phone: +49 241 80-21490
EMail: schaub@cs.rwth-aachen.de

Rooms

We are located on the 1st floor of E2, Computer Science Center

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