معرفی
Prof. Dr. Ingo Scholtes is Chair of Machine Learning for Complex Networks at Julius-Maximilians-Universität Würzburg's Center for Artificial Intelligence and Data Science (CAIDAS). His research spans network science, graph machine learning, and computational social science, with applications in software engineering, ecology, biology, and physics. He received a Juniorfellowship from the German Informatics Society (2014) and an SNSF Professorship (CHF 1.5Mio, 2018).
- Current affiliations: JMU Würzburg (since 2021), University of Zurich (2018-2024), Bergische Universität Wuppertal (2019-2021)
- Research focus: Higher-order network modeling, temporal graph analysis, AI for collaborative systems, causality-aware machine learning
His recent publications demonstrate strong trends in temporal network analysis, graph neural networks for time-series, and higher-order models across software engineering and social science domains. He co-chairs multiple international workshops on complex networks and serves as associate editor for EPJ Data Science and Advances in Complex Systems.
- Key scientific contributions: Foundational work on higher-order network models published in Nature Physics
- Methodological innovations in temporal network visualization (HOTVis) and path-based analysis (pathpy)
As both educator and organizer, he leads the Computational Social Science Section at GI e.V., mentors across disciplines, and develops tools like git2net for collaboration analysis. His work bridges theoretical foundations with practical applications in network science.
