School of Information News

Three new faculty members will join the School of Information in September. Jeff MacKie-Mason, associate dean for academic affairs, lauded the new hires as “stellar” individuals who will contribute immediately as assistant professors. They are Eytan Adar, Erin Krupka, and Qiaozhu Mei.

Eytan Adar
Ph.D., University of Washington

Adar is already viewed as an international leader in Internet-scale systems. He works on temporal informatics: the study of the change of information — and our consumption of it — over time. As one example, he is the principal designer of Zoetrope, a way of interacting with the Web that takes into account the fact that Web pages change frequently and it is nearly impossible to find data or follow a link after the underlying page evolves.

For example, the New York Times Web page  shows different news content that is updated nearly constantly. In current search engines, all that one can do is access a snapshot of the current state of a Web page. That fact limits the kinds of questions the user can ask on the Web. Zoetrope enables interaction with the historical Web that would otherwise be lost to time by allowing users to interact with content streams. That is,  users can look back though previous versions of Web pages and generate visualizations and extractions of the temporal data. A video of this work is available.

Adar has also done important work on a range of other topics, including social network analysis, where, for instance, he developed a mechanism for finding corporate expertise by analyzing the structure of E-mail exchanges.

Adar received his BS and M.Eng. from MIT, and his Ph.D. from the University of Washington, where he has had both an NSF Fellowship and an ARCS Fellowship. He has been employed at the Information Dynamics Lab at Hewlett Packard and as an intern and consultant at Microsoft Research. Although he just completed his Ph.D., he has already been author or co-author on more than 30 peer-reviewed publications, including two that won best paper awards.

Erin Krupka
Ph.D., Carnegie Mellon University

Krupka is an experimental behavioral economist who explores the ways in which social and environmental factors influence behavior, using both laboratory and field experiments. Her research on social norms suggests why individuals might engage in behaviors that appear inconsistent with self-interest and suggests why trivial modifications to a decision context can change behavior significantly.

She has shown in lab experiments that individuals behave in a manner consistent with social norms, even in settings where there is no strategic advantage for doing so. Broadly, her work contributes to the emerging literature that models the sway of nonwealth factors on choice, by using social norms to raise the “psychological cost” of selfishness. This work is directly relevant to the incentive-centered design of information systems, an approach pioneered by faculty at the School of Information.

Krupka received a BA from Wheaton College, an MPA from the University of Chicago, and an MS and Ph.D. from Carnegie Mellon University. For the past two years, she has been a research associate at IZA in Bonn, Germany. She is the author of three journal publications and a half dozen additional working papers and works in progress.

Qiaozhu Mei
Ph.D., University of Illinois at Urbana-Champaign

Mei has expertise in real-world problems related to text information management, and in particular he specializes in information retrieval and text mining, applications on the Web, scientific literature, and other genres of text data. The dramatic growth of textual information available online has enabled both advanced research – for example, through the broad availability of scientific literature — and increased ease of everyday activities.

Search engines, as the most useful tools to help users find and access text information, have already made a huge impact in the real world. However, many challenges remain to be solved to make search more accurate, efficient, and intelligent, and to go beyond to discover, analyze, and summarize useful knowledge from the information found. Mei’s research is aimed at developing both principled methodologies and innovative applications for automatically processing, managing, accessing, analyzing, discovering knowledge from, and summarizing large-scale text information.

As an example, he is one of the leaders in the field of contextual text mining, in which the context of a piece of text — for example, the time and location at which it was written, or the citation network of the author — is made an explicit part of the analysis. He has also worked on topics ranging from the use of language modeling in information retrieval to aspects of automatic tagging of objects on the Web.

Mei received a BS from Peking University and his Ph.D. at the University of Illinois at Urbana-Champaign. At Illinois, he held a number of prestigious scholarships, including the Yahoo! Ph.D. Student Fellowship, for which he was one of five recipients in the nation. He has held research internships at Yahoo! Research and Microsoft Research and been author or co-author of nearly 20 peer-reviewed publications.