Data stream algorithms and applications
S. MUTHUKRISHNAN
Rutgers/AT&T Shannon Labs
Friday, March 12, 2004
11-12, room 1504, HKUST




Abstract
--------
There are emerging applications where data arrives at 
great rate and high volume; it is difficult or
impossible to store all the data and to analyze such 
streams.  The theory of data stream algorithms is being 
developed to address this challenge. This talk will
provide an overview of data stream algorithms and 
discuss applications to IP network traffic 
data analysis, very large databases, analysis of massive 
biological sequences, etc. 


Biographical Sketch
-------------------
S. MUTHUKRISHNAN received his PhD from the Courant Institute 
in 1994. He has been a Lecturer at the University of Warwick, a 
Principal  Technical Staff at ATT Research Shannon Labs and is 
now an Associate Professor at Rutgers University.  His research 
interests include Applied Algorithms, Networking, Data Bases, String 
Pattern Matching and Probabilistic Methods. He was an invited plenary 
speaker (on mining data streams) at both the 2003 SIAM Conference
on Data Mining (SDM) and the 2003 Symposium on Discrete Algorithms (SODA).