CIIR Talk Series: Susan Dumais

Speaker: Susan Dumais, Technical Fellow and Director of the Microsoft Research Labs in New England, New York City and Montréal

Talk Title: The Potential for Personalization in Search

Date: Friday, December 4, 2020 - 1:00 - 2:00 PM EST (North American Eastern Standard Time) via Zoom

Talk Hosted by the CIIR and the Center for Data Science

Zoom Access: Zoom Link and reach out to Alex Taubman for the passcode.

Abstract: Traditionally Web search engines returned the same results to everyone who asks the same question. However, using a single ranking for everyone in every context at every point in time limits how well a search engine can do in providing relevant information. In this talk I present a framework to quantify the "potential for personalization” which is used to characterize the extent to which different people have different intents for the same query. I describe several examples of how different types of contextual features are represented and used to improve search quality for individuals and groups. Finally, I conclude by highlighting important challenges in developing personalized systems at Web scale including privacy, transparency, serendipity, and evaluation.

Bio: Susan Dumais is a Technical Fellow and Director of the Microsoft Research Labs in New England, New York City and Montréal, and an adjunct professor at the University of Washington. Prior to joining Microsoft, she was a Member of Technical Staff at Bell Labs and Bellcore. Her research is at the intersection of human-computer interaction, information retrieval, and web and data science. A common theme that runs through her work is the importance of understanding and improving information systems from an interdisciplinary and user-centered perspective. She is a co-inventor of Latent Semantic Analysis, a well-known word embedding technique, which was designed to mitigate the disagreement between the words that authors use writing and those that searchers use to find information. Her research spans a wide range of topics in information systems, including email spam filtering, user modeling and personalization, context-aware information systems, temporal dynamics of information, and large-scale behavioral interactions. She has worked closely with several Microsoft product teams (Bing, Windows Search, SharePoint, and Office Help) on search-related innovations, and has published widely in the fields of information retrieval, human-computer interaction, and cognitive science.

She is an ACM Fellow, was elected to the ACM SIGCHI Academy, the National Academy of Engineering (NAE), and the American Academy of Arts and Sciences (AAAS). She received the ACM Athena Lecturer Award for fundamental contributions to computer science, the SIGIR Gerard Salton Award for lifetime achievement in information retrieval, the Tony Kent Strix Award for outstanding contributions to information science, the ACM SIGCHI Research Award for lifetime achievement in human-computer interaction, and the lifetime achievement award from Indiana University Department of Psychological and Brain Science.