ACM Distinguished Speaker Talks- Sorting in Space

Posted by Sneha Shukla

Getting students and faculty alike excited about new technologies, and latest cutting edge ideas in the technological world is part of the culture at IIIT-D. ACM Distinguished Speaker series is a step in the direction of serving this purpose. Ever since the first talk at our inaugural event a year back, we have been getting requests for another talk. So here we are, with the second ACM Distinguished Speaker Talk.

As a part of the series, we were fortunate to have amongst us Prof. Hanan Samet, from the University of Maryland (http://www.cs.umd.edu/~hjs/). A PhD. from Stanford University, Prof. Samet is a member of the Computer Vision Laboratory at the Center for Automation Research where he leads a number of research projects on the use of hierarchical data structures for database applications involving spatial data. His recent book “Foundations of Multidimensional and Metric Data Structures” published by Morgan-Kaufmann, San Francisco, CA, in 2006 (http://www.mkp.com/multidimensional), is an award winner in the 2006 best book in Computer and Information Science competition of the Professional and Scholarly Publishers (PSP) Group of the American Publishers Association (AAP). The founding chair of ACM SIGSPATIAL, and an ACM Distinguished Speaker, the talk by Prof. Samet was attended in abundance by students and teachers alike.

In his talk, Prof. Samet gave a brief overview of hierarchical spatial data structures and related research results. There was also a demonstration of the SAND Browser (found at http://www.cs.umd.edu/~brabec/sandjava) and the VASCO JAVA applet which illustrate these methods (found at http://www.cs.umd.edu/~hjs/quadtree/index.html).

The representation of spatial data is an important issue in computer graphics, computer vision, geographic information systems, and robotics. A wide number of representations is currently in use. Recently, there has been much interest in hierarchical data structures such as quadtrees, octrees, R-trees, etc. The key advantage of these representations is that they provide a way to index into space.  In fact, they are little more than multidimensional sorts.  They are compact and depending on the nature of the spatial data they save space as well as time and also facilitate operations such as search.

I immensely enjoyed the talk, although to be honest, the ideas were a little too baffling for me at first! But the talk successfully served it’s purpose. Today, I love to get my hands onto any additional information that I can hierarchical spatial data structures! Thanks Dr. Samet and ACM!!