Topic: Perspective on Link Prediction
Speaker: Nitesh Chawla,email@example.com,University of Notre Dame, USA,
Time: 24th, May, 15:00-16:00
Location: FIT 1-315
Abstract: 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 single and multi-relational 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 the Interdisciplinary Center for Network Science and Applications (iCeNSA) and Director of Data Inference Analysis and Learning Lab (DIAL). 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, DARPA, and a number of Industry Sponsors, bringing in over $8 Million in research funding. He is the chair of the IEEE CIS Data Mining Technical Committee.