The Rudi Studer Lab

Rudi Studer’s lab focuses on the design and application of knowledge-based and semantic technologies for intelligent information systems. The core research goal is to enable machines and humans to better understand, integrate, and reason over complex, heterogeneous data at scale. A central theme of the lab is the Semantic Web and Linked Data, including entity-centric data integration, data fusion, knowledge graphs, and ontology-based modeling. The lab develops methods to integrate structured and unstructured data from distributed sources, making information more transparent, interoperable, and trustworthy. Another key area is smart and cognitive services, where web services are enriched with reasoning, context awareness, and autonomous decision logic to support complex tasks. Research frequently targets real-world application domains such as digital media analysis, political communication, healthcare, and service systems. Examples include data-driven analysis of political bias in news media, semantic infrastructures for medical decision support, and intelligent service platforms that combine data, rules, and domain knowledge. The work has strong societal relevance by promoting transparency in public discourse, improving decision-making in critical domains like medicine, and enabling more efficient digital services. The lab is well suited for students interested in computer science, information systems, or data science. Ideal candidates enjoy working with data, knowledge representation, and AI methods, and are motivated to build systems that bridge theory and impactful real-world applications.