Our research is focused on developing intelligent technology to connect people to information. Topics include search engines, recommender systems, and conversational assistants. We follow a data-driven, machine learning-based approach to contribute to fundamental knowledge in the area of information retrieval with new algorithms, new models, and new evaluation methodology.       

Topic areas: information retrieval, search engine, recommender system, conversational assistant


My research is focused on building the necessary methods and technology to enable human – machine collaboration for retrieving information by obtaining a deeper understanding of user preferences and decisions during information seeking activities, developing algorithms that can interact with users during information seeking activities, and building the appropriate evaluation methodology to measure progress.

Topic areas: information retrieval, recommender systems, conversational AI, language technology

My research is focused on improving content-based and domain-specific search, in order to better satisfy information needs for settings and tasks with limited interaction data. This research often follows a neural approach, building upon methods from deep learning and NLP like pre-trained transformers to better assess relevance based on textual inputs.

Topic areas: information retrieval, search engines, recommender systems


My research focus is on building information retrieval systems that effectively interact with users for understanding and modeling user information needs. This involves various research aspects with the user at its core, namely, studying human-computer interactions and proposing the next generation of interactive systems based on its findings.

Topic areas: information retrieval, search enginge, recommender system, conversational assistant, human computation