Ankur Gupta


Wisdom RFP Grant Recipient
Assistant Professor

Butler University

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Dr. Ankur Gupta is an Assistant Professor of Computer Science and Software Engineering at Butler University. He finished his PhD from Duke University in 2007 under the guidance of Dean Jeffrey Scott Vitter. Prior to that, Dr. Gupta finished a Bachelors in Mathematics, a Bachelors in Computer Science, and a Masters in Computer Science from the University of Texas at Dallas in 2000. Dr. Gupta’s research interests are broadly in the area of design and analysis of algorithms and data structures, with recent application to such topics as data compression, text indexing, and dynamic and streaming data.



Defining Wisdom project title:
Wisdom Is Compression: Data Compression as a Mathematical Measure of Wisdom

Project Description:
The world is drowning in data, and we are faced with the challenge of understanding it quickly and well. The idea of well-understood varies based on the data we have, but the universal goal is to sift the huge amount of information into its most essential components. This filtration process was considered a practical definition of wisdom by a number of thinkers in the Victorian Age. In their view, wisdom serves as a verifiable process of cognitive thought with respect to the real world. This pragmatic definition corresponds strongly with the nature of information from a computer scientist’s perspective, and in particular, to the task of compression. In an increasingly technical world, it is of critical importance to update our notions of wisdom to incorporate a new information-processing aspect to wisdom. It is no longer sufficient to consider a model where wisdom is dispensed by a human expert to a single individual. Computers can retain huge amounts of information and process it to find the answer to any question contained therein -- why disallow the concept of wisdom in this case? Careful organization of the data may address both the speed issue and the quality of the result; the organization requiring the least amount of memory capacity may be termed as wisdom. In this project, we draw a parallel between the definition of wisdom and compression, which is often achieved by reorganizing data to reduce redundancy.



Recent Publications
On searching compressed string collections cache-obliviously
Ferragina, P., Grossi, R., Gupta, A., Shah, R., & Vitter, J. S. Proceedings of the ACM Conference on Principles of Database Systems (PODS), Vancouver, Canada, May 2008. Abstract: Current data structures for searching large string collections either fail to achieve minimum space or cause too many cache misses. In this paper we discuss some edge linearizations of the classic trie data structure that are simultaneously...
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Institution

Butler University

Current Position

Assistant Professor

Highest Degree

PhD Computer Science

Research Interests


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