Gautam Das (computer scientist)

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Gautam Das
Alma materUniversity of Wisconsin, Madison
Indian Institute of Technology, Kanpur
Known for
Awards
Scientific career
FieldsComputer Science
InstitutionsMicrosoft Research
Compaq
University of Memphis
University of Texas at Arlington
ThesisApproximation Schemes in Computational Geometry (1990)
Doctoral advisorDeborah A. Joseph
Websiteranger.uta.edu/~gdas

Gautam Das[1] is a computer scientist in the field of databases research. He is an ACM Fellow (since 2021) and IEEE Fellow (since 2020).

He is a Distinguished University Chair Professor of Computer Science and Engineering, Associate Dean of Research of College of Engineering at the University of Texas at Arlington, and director of the Database Exploration Laboratory (DBXLAB) at the CSE department at UTA. His is known for his work in databases, data mining, computational geometry, and algorithms.

Biography[edit]

He graduated with a B.Tech. in computer science from IIT Kanpur, India, and with a Ph.D. in computer science from the University of Wisconsin, Madison. Prior to joining UTA in 2004, Das has held positions at Microsoft Research, Compaq and the University of Memphis.

Research[edit]

Das's early research interests were in computational geometry and graph algorithms. His Ph.D. dissertation[2] made several significant contributions, most notably the discovery of greedy graph spanners[3]. Greedy spanners – for general weighted graphs as well as in the geometric setting – have been continuously and extensively studied ever since, and have been shown to be almost as good as any other graph spanner in both lightness and edge sparsity.

In the subsequent decades, his research interests broadened to all aspects of Big Data Exploration, including data management, data analytics, machine learning and data mining. He contributed to early research on the intersection of databases and information retrieval, in particular keyword search (e.g., the DBXplorer system[4]) and ranked retrieval[5] in database systems. Other highlights of his research have been in time series mining[6], approximate query processing[7], and Deep Web analytics[8]. He is presently working on areas such as machine learning approaches for approximate query processing, and fairness and explainability in data management systems.[citation needed]

His work has received several awards, including the Communications of ACM Research Highlight in 2021[9], Research Highlight Award of SIGMOD 2019, ACM SIGKDD Doctoral Dissertation Award (honorable mention) in 2014 (for his student)[10], IEEE ICDE 10-Year Influential Paper award received in 2012[4], and numerous other awards.[citation needed]

Gautam Das has been on the editorial board of the journals ACM TODS and IEEE TKDE. He has served in the organization roles of several major conferences, including as General Chair of ACM SIGMOD/PODS 2018.[citation needed]

See also[edit]

References[edit]

  1. ^ "Gautam Das". ranger.uta.edu. Retrieved 19 June 2019.
  2. ^ Das, Gautam. Approximation schemes in computational geometry. OCLC 22935858.
  3. ^ Althöfer, Ingo; Das, Gautam; Dobkin, David; Joseph, Deborah; Soares, José (1993), "On sparse spanners of weighted graphs", Discrete & Computational Geometry, 9 (1): 81–100, doi:10.1007/BF02189308, MR 1184695
  4. ^ a b Agrawal, Sanjay; Chaudhuri, Surajit; Das, Gautam (2002), "DBXplorer: A system for keyword-based search over relational databases", Proceedings 18th International Conference on Data Engineering, pp. 5–16, CiteSeerX 10.1.1.114.5479, doi:10.1109/ICDE.2002.994693, ISBN 0-7695-1531-2, S2CID 3832378
  5. ^ Agrawal, Sanjay; Chaudhuri, Surajit; Das, Gautam; Gionis, Aristides (2003), "Automated Ranking of Database Query Results" (PDF), CIDR 2003, First Biennial Conference on Innovative Data Systems Research, Asilomar, CA, USA, January 5-8, 2003, Online Proceedings
  6. ^ Das, Gautam; Lin, King-Ip; Mannila, Heikki; Renganathan, Gopal; Smyth, Padhraic (1998), "Rule Discovery from Time Series" (PDF), Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), New York City, New York, US, August 27–31: 16–22
  7. ^ Chaudhuri, Surajit; Das, Gautam; R. Narasayya, Vivek (2007), "Optimized stratified sampling for approximate query processing", ACM Transactions on Database Systems, 32 (2): 9, CiteSeerX 10.1.1.107.8286, doi:10.1145/1242524.1242526, S2CID 7211932
  8. ^ Dasgupta, Arjun; Das, Gautam; Mannila, Heikki (2007), "A random walk approach to sampling hidden databases", Proceedings of the 2007 ACM SIGMOD international conference on Management of data, pp. 629–640, doi:10.1145/1247480.1247550, hdl:10106/96, ISBN 9781595936868, S2CID 14078452
  9. ^ Asudeh, Abolfazl; Augustine, Jees; Thirumuruganathan, Saravanan; Nazi, Azade; Zhang, Nan; Das, Gautam; Srivastava, Divesh (25 January 2021). "Scalable signal reconstruction for a broad range of applications" (PDF). Communications of the ACM. 64 (2): 106–115. doi:10.1145/3441689. ISSN 0001-0782.
  10. ^ "SIGKDD Awards : 2014 SIGKDD Dissertation Award Winners". www.kdd.org. Retrieved 19 June 2019.
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