Vikas Garg, Electrical Engineering & Computer Science
Massachusetts Institute of Technology
Christian Gorenflo, PhD candidate
David R. Cheriton School of Computer Science
Anil Pacaci, PhD candidate
David R. Cheriton School of Computer Science
Jan Gorzny, PhD candidate
David R. Cheriton School of Computer Science
Nashid Shahriar, PhD candidate
David R. Cheriton School of Computer Science
Mike Schaekermann, PhD candidate
David R. Cheriton School of Computer Science
Artificial intelligence (AI) assistants for clinical decision making show increasing promise in medicine. However, medical assessments can be contentious, leading to expert disagreement. This raises the question of how AI assistants should be designed to handle the classification of ambiguous cases.
Mina Farid, PhD candidate
David R. Cheriton School of Computer Science
One challenge that faces most extraction tools is the long tail of information. Entities that lie in the long tail do not have enough mentions in the text, limiting their relevant context. The absence of enough repetition restricts the extraction of property values with high confidence.
Sasha Vtyurina, PhD candidate
David R. Cheriton School of Computer Science
Voice-based assistants have become a popular tool for conducting web search, particularly for factoid question answering. However, for more complex web searches their functionality remains limited, as does our understanding of the ways in which searchers can best interact with audio-based search results.
Mina Farid, PhD candidate
David R. Cheriton School of Computer Science
Kimon Fountoulakis, Assistant Professor
David R. Cheriton School of Computer Science