Our work brings together research expertise in information retrieval (IR), natural language processing and data science. We focus on core IR topics such as collaborative search, conversational search and data-hungry ranking models. We also focus on the application of IR to various domains, most prominently the educational domain.
With this topic, we aim at improving the search platforms to better enable people to learn whilst searching.
We move from the paradigm of small-group collaborative searching to large-group collaborative searching.
With this research topic, we investigate how to perform searching via a conversation with a conversational agent.
We investigate methods for rule extraction from regulatory documents.
We are interested in researching and dissecting neural IR approaches.