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CS Colloquium 4/17/2013 "Mining Complex Graphs and Networks"Posted Mar. 27, 2013
Mining Complex Graphs and Networks
Dr. Mohammed J. Zaki, Ph.D.
Department of Computer Science
Rensselaer Polytechnic Institute
Troy, New York
April 17th@ 3:45 p.m. 228 MSB
Data, data, everywhere, but not any drop of insight! Many real world problems can be effectively modeled as complex relationship networks or graphs where nodes represent data entities of interest and edges mimic the interactions or relationships among them. However, taming the complexity and scalability is essential for knowledge discovery. In this talk, I will highlight some of our recent work on mining complex patterns such as attributed subgraphs, boolean expressions, and so on, based on random sampling strategies. I will also outline related work in graph indexing. Finally, I will conclude with thoughts on directions for the future.
Mohammed J. Zaki is a Professor of Computer Science at RPI. He received his Ph.D. degree in computer science from the University of Rochester in 1998. His research interests focus on developing novel data mining techniques, especially for social networks and bioinformatics. He has over 200 publications in data mining and bioinformatics. He is currently Area Editor for Statistical Analysis and Data Mining, and an Associate Editor for Data Mining and Knowledge Discovery, ACM Transactions on Knowledge Discovery from Data, Knowledge and Information Systems, Social Networks and Mining, and International Journal of Knowledge Discovery in Bioinformatics. He was the program co-chair for SDM'08, SIGKDD'09, PAKDD'10, BIBM'11, CIKM'12, and ICDM'12, and he is the founding co-chair for the BIOKDD workshop. He received several research awards, such as the NSF CAREER Award, DOE Career Award, HP Innovation Research Award, and Google Faculty Research Award. He is a senior member of the IEEE, and an ACM Distinguished Scientist.