Brief Bio

Jeff Z. Pan is Professor of Knowledge Computing in the School of Informatics at The University of Edinburgh. He is a chair of the Knowledge Graph Group at the Alan Turing Institute. He received his PhD in Computer Science from the University of Manchester. Before joining Edinburgh in 2020, he was a faculty member in the Department of Computing Science at the University of Aberdeen, where he led the Knowledge Technology Group and directed the Joint Research Lab on Knowledge Engineering and Information Security.

Jeff's research focuses on Knowledge Computing and Artificial Intelligence, particularly knowledge-enhanced learning and reasoning, knowledge-grounded natural language understanding and generation, model fusion and editing, and knowledge memorisation. His work spans applications in information retrieval, healthcare, software engineering and open science. His current research explores how long-term autonomous AI systems can leverage shared and evolving knowledge to achieve reliable behaviour, collaborative discovery and continual adaptation.

Jeff has made significant contributions to bridging symbolic knowledge representation and modern AI. In 2023, he was the lead author of Large Language Models and Knowledge Graphs: Opportunities and Challenges (TGDK), an influential international position paper that highlighted the complementary strengths of explicit knowledge in knowledge graphs and parametric knowledge in LLMs, helping shape a research agenda for their integration. This work builds on his longstanding research in knowledge representation, automated reasoning and knowledge-based intelligent systems, connecting foundational advances in knowledge computing with emerging developments in generative AI.

Jeff led the development of the award-winning TrOWL reasoner, which was integrated with Oracle Spatial and Graph (from version 12) through the OWL-DBC database connection. As an internationally recognised expert in Knowledge Graphs, he served as chief editor and principal author of the first book dedicated to knowledge graphs, now a foundational technology widely adopted by leading IT companies, including Google, IBM, Meta, Amazon and Microsoft. As Chief Scientist and Coordinator of K-Drive, a pioneering EU Marie Curie project on Knowledge Graphs, he coordinated more than 20 Marie Curie Fellows, including researchers from IBM and Expert System. He also serves as an editor of Transactions on Graph Data and Knowledge (TGDK) and IEEE Transactions on Cognitive and Developmental Systsems (TCDS) and was a Programme Chair of the 19th International Semantic Web Conference (ISWC 2020), a premier international forum for the Semantic Web, Knowledge Graph and Linked Data communities.

Together, these contributions reflect a sustained research vision: advancing knowledge computing from foundational representation and reasoning to knowledge-enhanced AI, and ultimately towards long-running autonomous systems that can reliably reason, collaborate, adapt and continually improve through shared and evolving knowledge.