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Niketan Pansare

  • Phd Student @ Rice university
  • 3h-indexImpact measure calculated using publication and citation counts. Updated daily.
  • 207CitationsNumber of citations received by Niketan's publications. Updated daily.

Recent publications

  • Topic models over spoken language

    • Pansare N
    • Jermaine C
    • Haas P
    • et al.
    Get full text
  • Online Aggregation for Large MapReduce Jobs

    • Pansare N
    • Borkar V
    • Jermaine C
    • et al.

Professional experience

Research Intern

IBM India Research Lab

May 2011 - July 2011(2 months)

Software Developer Intern @ SQL Server


May 2008 - July 2008(2 months)

Software Engineer


August 2006 - April 2007(8 months)


Phd in Computer Science

Computer Science, Rice University

August 2009 - May 2012(3 years)

Masters of Science

University of Florida

August 2007 - July 2009(2 years)

Bachelor of Engineering


August 2002 - June 2006(4 years)

Diploma in Embedded Systems

Electronic Co-operation of India Limited (ECIL)

October 2003 - February 2004(4 months)

IBM Research


At a very high level, I work in the field of Statistical Databases and Data Mining; and hence most of my research projects involve building systems for performing statistical analysis on large scale data. To address my research problems, I generally resort to Bayesian methodology and use scalable systems (like Hadoop, Hyracks and Datapath). A key problem that I am very excited about is providing online approximate answers on Map-Reduce systems. Though the problem of Approximate Query Processing has been studied extensively in the field of databases using sampling theory (See OLA97, Ripple Join and DBO), these traditional sampling techniques cannot be applied directly to Map-Reduce systems due to certain challenges (like inspection paradox). These are addressed in my VLDB paper, which also discusses a bayesian model to deal with these challenges.

Co-authors (21)

  • Nakul Jindal
  • Rolando Garcia-Milian
  • Christan Grant

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