AI Seminar

Perspective on Link Prediction

Nitesh Chawla

Associate Professor
University of Notre Dame
Tuesday, January 31, 2012
4:00pm - 5:30pm
3725 Beyster Bldg.

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About the Event

Link prediction is the task of predicting relationships in a network. As interest in network science grew, so did the realization of the broad applicability of general link prediction --- from security to collaboration to marketing to information flow to biology and medicine. Such broad applicability also brings forth a number of challenges to consider, including generality of methodologies, modes of evaluation, and scalability. In this talk, I shall offer a perspective on link prediction for both homogeneous and heterogeneous information networks, and present applications in social networks and biology/medicine.


Nitesh Chawla is an Associate Professor in the Department of Computer Science and Engineering, Director of Data Inference Analysis and Learning Lab (DIAL), and co-Director of the Interdisciplinary Center for Network Science and Applications (iCeNSA). His research is focused on machine learning, data mining, and network science with interdisciplinary connections to climate data sciences, healthcare informatics, and social networks. He is the recipient of multiple awards for research and teaching innovation including outstanding dissertation award, outstanding undergraduate Teacher in 2008 and 2011, National Academy of Engineers New Faculty Fellowship, and number of best paper awards and nominations. His research is currently supported by National Science Foundation, the Department of Energy, the Army Research Labs, and a number of Industry Sponsors. He is the chair of the IEEE CIS Data Mining Technical Committee.

Additional Information

Sponsor(s): Toyota

Open to: Public