Christoph Lange

Christoph Lange is the Head of the Data Science and Artificial Intelligence department at the Fraunhofer Institute for Applied Information Technology (FIT) and a senior researcher at the Chair of Information Systems 5 (DBIS) at RWTH Aachen University, Germany. He has been affiliated with RWTH Aachen since 2019 and with Fraunhofer since 2014.

He received his Ph.D. from Jacobs University Bremen in 2011 for work on enabling collaboration on semiformal mathematical knowledge through semantic web integration. His research focuses on knowledge engineering, data infrastructures, and semantic technologies, particularly aligned with Linked Data and FAIR principles (Findable, Accessible, Interoperable, Reusable). Applications span enterprise data integration, research infrastructures, and cross-organizational data spaces, with contractual R&D conducted for leading German and international automotive and industrial enterprises.

His research interests include Knowledge Engineering, Semantic Web, Knowledge Graphs, Ontology Engineering, FAIR Data, and Intelligent Computer Mathematics. He has co-supervised 10 PhD students and taught courses such as the Knowledge Graph Lab at RWTH Aachen. He has organized numerous conferences, workshops, and training events in semantic web and intelligent mathematics domains and contributed to W3C and OMG international standards.

Recent publications (2023–2025) demonstrate a strong trend towards integrating Large Language Models with semantic technologies for FAIR data spaces, ontology development, and explainable AI. His work also advances tools for knowledge graph creation (e.g., KGraphX), RDF validation, federated data catalogues, and semantic interoperability in manufacturing and scientific domains.

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Christoph Lange has served as an expert reviewer for international funding bodies and has led impactful collaborations across academia and industry. His work bridges theoretical advances in knowledge representation with real-world applications in data-intensive sectors. He is actively involved in research projects such as NFDI4DS and FAIR Data Spaces, contributing to next-generation data ecosystems.

He leads the development of semantic tools and infrastructures, including contributions to Wikidata and CEUR-WS semantification. His lab work includes the Knowledge Graph Lab series, focusing on practical implementation and teaching of semantic technologies. Future work is expected to further explore the synergy between generative AI and formal knowledge representation to enhance data quality, reuse, and machine understanding.