Google Tech Talks
January, 23 2008
I will describe some algorithms for addressing some fundamental optimization
problems that arise in the context of data storage and management. In the
first part of the talk we will address the following question: How should
we store data in order to effectively cope with non-uniform demand for
data? How many copies of popular data objects do we need? Where should
we store them for effective load balancing?
In the second part of the talk we will address the issue of moving
data objects quickly, to react to changing demand patterns. We will
develop approximation algorithms for these problems.
The first part of the talk is joint work with Golubchik, Khanna,Thurimella and Zhu. The second part is joint work with Kim and Wan.
Speaker: Samir Khuller
Samir Khuller received his M.S and Ph.D from Cornell University in 1989
and 1990, respectively. He spent 2 years as a Research Associate at the
Institute for Advanced Computer Studies at the University of Maryland,
before joining the Computer Science Department in 1992, where he is a Professor
and Associate Chair in the Department of Computer Science.
His research interests are in graph algorithms, discrete optimization, and
computational geometry. He has published about 130 journal and conference
papers, and several book chapters on these topics.
He received the National Science Foundation's Career Development Award,
the Dean's Teaching Excellence Award and also a CTE-Lilly Teaching Fellowship.
In 2003, he and his students were awarded the "Best newcomer paper" award for
the ACM PODS Conference. He received the University of Maryland's
Distinguished Scholar Teacher Award in 2007.