Dr. Jamie Callan is a Professor at Carnegie Mellon University's Language Technologies Institute (LTI), where he leads research in information retrieval. He is recognized for his contributions to advanced search engine architectures, federated retrieval, and neural approaches to document ranking. He has published more than 200 papers on these and related topics.

Jamie’s current research focuses on leveraging neural techniques and large language models to enhance information retrieval systems, including improvements in term weighting, conversational retrieval, and retrieval-augmented generation. His recent research includes improved first stage retrieval using a latent vocabulary for sparse systems and hypothetical documents for dense vector-based systems. He also maintains and distributes the widely used ClueWeb datasets, which have supported the research community for more than a decade.

His scientific service includes senior program committee member and area chair for conferences such as SIGIR, WSDM, and ECIR. He is a past Treasurer and past Chair of SIGIR, the international professional society for Information Retrieval research, a co-founding Editor-in-Chief of Foundations and Trends in Information Retrieval, and a past Editor-in-Chief of ACM's Transactions on Information Systems (TOIS).

Jamie teaches a course on search engine design and advises students across several programs. He is also the LTI's Ph.D. Program Director.

Updated on February 18, 2025