We research information retrieval — from formal models and neural ranking to large language models and health search — building search technologies that help people find better answers and make better decisions.
Retrieval models, learning to rank, dense and neural retrieval, user models, and the rigorous evaluation of information retrieval systems.
Consumer health search, clinical decision support, precision medicine, search for systematic review compilation, and cohort selection for clinical trials.
Large language models for retrieval and ranking, safe and reliable generative IR, conversational search, and domain-specific search such as case law retrieval.
Our ARC Discovery Project 2021 “AI-driven Effective Query Formulation for Better Systematic Reviews.” has been accepted for funding. This project extend the initial work we have...
We are seeking a Postdoctoral Research Fellow that will contribute to innovative research developments within the scope of digital health. The project aims to devise new method ...
We are seeking a Postdoctoral Research Fellow that will contribute to innovative research developments within the scope of conversational search. The project the postdoc will be...
ielab brings together 17 researchers at The University of Queensland and collaborators at CSIRO, the University of Strathclyde, and beyond. If you are interested in information retrieval, come and have a chat!
