Interdisciplinary Research on Graphs, Networks, and Connectivity Structures

Graphs and networks represent complex relationships in various fields, including social sciences, biology, transportation, computer networks, recommendation systems, and computer graphics. InterConnect will foster interaction between these communities.

Graph neural networks and topological data analysis provide strong potential for gaining deeper insights into global patterns in graph-structured data, utilizing a combination of ML, combinatorics, geometry, algebra, and statistics techniques. Studying these networks’ connectivity provides insights into information flow, social dynamics, disease spread, traffic optimization, network resilience, and much more. InterConnect will stimulate novel research ideas in these fields by promoting and enhancing networks between TUM researchers and scientists worldwide.

Workshops and conferences

InterConnect PIs co-organize the ICCV 2023 workshop on Scene Graphs and Graph Representation Learning and are hosting the Munich meetup of the Leaning on Graphs Conference 2023. They will initiate a workshop at the TUM Science & Study Center in Raitenhaslach for internal and external PIs and junior researchers.

Teaching

New joint lectures by multiple PIs and block seminars for master’s students represent innovative formats, especially because they target students from different schools. In the future, InterConnect plans to host a summer school in Munich on graphs and networks.