Data stream algorithms are algorithms that perform computation over streams of data using only a limited amount of space. The field has experienced a significant growth over the last decade. Data stream algorithms have found applications in many domains, including analysis of massive data sets and network monitoring. At the same time, the field has been enriched by the discovery of strong connections to other areas, such as metric embeddings, communication complexity and compressed sensing.

This talk will provide an overview of streaming algorithms and related concepts.

Host: Richard Baraniuk

Biography of Piotr Indyk:
Piotr Indyk joined MIT in September 2000, after earning PhD from Stanford University. Earlier, he received Magister degree from Uniwersytet Warszawski in 1995. As of July 2007, he holds the title of Associate Professor with Tenure in the Department of Electrical Engineering and Computer Science.

Piotr's research interests include: computational geometry (especially in high dimensional spaces), algorithms using sublinear time and/or space and streaming algorithms. He is also interested in algorithmic coding theory and pattern matching problems.

Piotr is a recipient of NSF CAREER Award (2002), Sloan Fellowship (2003) and Packard Research Fellowship (2003).