Farhan Tauheed's talk on DB Seminar

Title: Accelerating Range Queries For Brain Simulations

 

Abstract

Neuroscientists increasingly use computational tools to build and simulate models of the brain. The amounts of data involved in these simulations are immense and the importance of their efficient management is primordial.

 

One particular problem in analyzing this data is the scalable execution of range queries on spatial models of the brain. Known indexing approaches do not perform well, even on today’s small models containing only few million densely packed spatial elements. The problem of current approaches is that with the increasing level of detail in the models, the overlap in the tree structure also increases, ultimately slowing down query execution. The neuroscientists’ need to work with bigger and more importantly, with increasingly detailed (denser) models, motivates us to develop a new indexing approach. To this end we developed FLAT, a scalable indexing approach for dense data sets. We based the development of FLAT on the key observation that current approaches suffer from overlap in case of dense data sets. We hence designed FLAT as an approach with two phases, each independent of density. 

 

Bio

Farhan Tauheed received his under graduate degree in computer science with distinction from National University of Conmputer and Emerging Sciences, Pakistan. He did his M.S in Computer Science from Lahore University of Management Sciences, Pakistan. Currently, he is pursuing his PhD study in DIAS lab and Blue Brain project in the life sciences department EPFL. His research interests include working with spatial data processing algorithms and data intensive life science problems.

 

He was awarded complete merit scholarship for Bachelors and Masters study from the Ministry of Science and Technology Pakistan. Prior to his PhD study he was also involved in working with Frontiers publication journal as a software engineer. He is an avid traveler and an amateur landscape photographer.