Michael Schaub

Michael Schaub is a tenure-track Assistant Professor in the Department of Computer Science at RWTH Aachen University, specializing in Computational Network Science. His research focuses on analyzing complex systems through network and graph models, integrating dynamical systems, control theory, and machine learning. He leads the Computational Network Science group, advancing methodologies for higher-order network models like simplicial complexes and hypergraphs. Schaub holds a PhD from Imperial College London and has held postdoctoral positions at MIT and Oxford. He is an ERC Starting Grant recipient (2022) and a Marie Curie Fellow, recognized for contributions to network dynamics and topological data analysis.

Education:

• PhD in Mathematics, Imperial College London (2011-2015)
• MSc in Biomedical Engineering, Imperial College London (2010)
• BSc in Electrical Engineering, ETH Zurich (2007-2010)

Research Interests: Schaub’s work spans interdisciplinary applications of network science, including biological systems, social networks, and technical infrastructures. Key areas include:

• Higher-order network models (hypergraphs, simplicial complexes)
• Graph signal processing and dynamics on networks
• Community detection and dynamical systems analysis
• Topological data analysis and machine learning

Grants & Awards:

• ERC Starting Grant (2022): HIGH-HOPeS project
• Marie Skłodowska-Curie Fellowship (2017-2019)
• Junior Fellow, German Informatics Society (GI)
• Member of Junges Kolleg (North Rhine-Westphalia Academy)

Labs & Teams: Leads the Computational Network Science Lab at RWTH Aachen, collaborating internationally on projects like the ELLIS Society and the European Laboratory for Learning and Intelligent Systems (ELLIS). Active in organizing workshops (e.g., Toponets, SIAM MDS).