معرفی
Craig Macdonald is a Professor of Information Retrieval in the School of Computing Science at the University of Glasgow. His research focuses on information retrieval across diverse domains, including web, enterprise systems, social media, and smart cities. He has led projects like the SMART FP7 initiative, developing a search engine integrating sensor and social media data. Macdonald is a core developer of the Terrier IR platform and has contributed to TREC tracks such as Blog, Microblog, and Web. His PhD thesis addressed expertise search in enterprise environments, leading to practical systems like the SICSA expert search tool. He has organized conferences including CIKM 2011 and contributed to BCS IRSG and ACM SIGIR. His work spans theoretical advancements and applied systems, emphasizing reproducibility and open-source tools like PyTerrier.
Education: BSc (1st Class Honours) in Computing Science (2004), PhD in Information Retrieval (completed).
Research Interests: Expert search, blog/web/enterprise IR, sensor data integration, and recommendation systems. Notable projects include the SMART search engine for smart cities and contributions to TREC's Web track since 2014. He has also pioneered methods in query expansion, diversification, and sensitivity review systems.
Publications (selected): Over 150+ papers in top venues like SIGIR, CIKM, and ECIR, focusing on retrieval models, recommendation systems, and evaluation frameworks. His work on RAG pipelines, pruning techniques, and contextual recommendation has driven practical advancements in AI-driven IR.
