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Computer Science

D-Index
62
Citations
14112
World Ranking
2928
National Ranking
1439

Overview

Vivek Narasayya is affiliated with Microsoft in the United States and has contributed extensively to the field of Computer Science. Their research spans several subfields including Computer Networks and Communications, Signal Processing, Artificial Intelligence, Information Systems, and Management Science and Operations Research.

The scientist's work primarily focuses on areas such as Advanced Database Systems and Queries, Data Management and Algorithms, Cloud Computing and Resource Management, Data Quality and Management, Distributed and Parallel Computing Systems, Distributed Systems and Fault Tolerance, and IoT and Edge/Fog Computing.

Vivek Narasayya has published numerous papers, with notable recent contributions including:

  • "Efficiently approximating selectivity functions using low overhead regression models" (2020), Proceedings of the VLDB Endowment
  • "DSB" (2021), Proceedings of the VLDB Endowment
  • "Budget-aware Index Tuning with Reinforcement Learning" (2022), Proceedings of the 2022 International Conference on Management of Data
  • "Cloud Data Services: Workloads, Architectures and Multi-Tenancy" (2021), Foundations and Trends in Databases
  • "ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning" (2022), Proceedings of the 2022 International Conference on Management of Data

Frequent co-authors in their collaborations include Surajit Chaudhuri, Tarique Siddiqui, Wentao Wu, Xiaoying Wang, and Bailu Ding. These partnerships have contributed to a range of research projects and publications.

The main venues where Vivek Narasayya has published include:

  • Proceedings of the VLDB Endowment
  • arXiv (Cornell University)
  • Proceedings of the 2022 International Conference on Management of Data
  • Foundations and Trends in Databases
  • Proceedings of the ACM on Management of Data

This body of work demonstrates activity across a range of topics and venues commonly associated with database systems, data management, and cloud computing research, reflecting a comprehensive engagement with both theoretical and applied aspects in these areas.

Best Publications

  • An overview of business intelligence technology

    Surajit Chaudhuri;Umeshwar Dayal;Vivek Narasayya

  • Automated Selection of Materialized Views and Indexes in SQL Databases

    Sanjay Agrawal;Surajit Chaudhuri;Vivek R. Narasayya

  • Integrating vertical and horizontal partitioning into automated physical database design

    Sanjay Agrawal;Vivek Narasayya;Beverly Yang

  • An Efficient Cost-Driven Index Selection Tool for Microsoft SQL Server

    Surajit Chaudhuri;Vivek R. Narasayya

  • On random sampling over joins

    Surajit Chaudhuri;Rajeev Motwani;Vivek Narasayya

  • Self-tuning database systems: a decade of progress

    Surajit Chaudhuri;Vivek Narasayya

  • AutoAdmin “what-if” index analysis utility

    Surajit Chaudhuri;Vivek Narasayya

  • Database tuning advisor for microsoft SQL server 2005: demo

    Sanjay Agrawal;Surajit Chaudhuri;Lubor Kollar;Arun Marathe

  • Random sampling for histogram construction: how much is enough?

    Surajit Chaudhuri;Rajeev Motwani;Vivek Narasayya

  • Database Tuning Advisor for Microsoft SQL Server 2005

    Sanjay Agrawal;Surajit Chaudhuri;Lubor Kollár;Arunprasad P. Marathe

  • Optimized stratified sampling for approximate query processing

    Surajit Chaudhuri;Gautam Das;Vivek Narasayya

  • Towards estimation error guarantees for distinct values

    Moses Charikar;Surajit Chaudhuri;Rajeev Motwani;Vivek Narasayya

  • Automating statistics management for query optimizers

    S. Chaudhuri;V. Narasayya

  • What-if index analysis utility for database systems

    Surajit Chaudhuri;Vivek Narasayya

  • Overcoming limitations of sampling for aggregation queries

    S. Chaudhuri;G. Das;M. Datar;R. Motwani

  • Trace based method for the analysis, benchmarking and tuning of object oriented databases and applications

    Henry M. Levy;Ashutosh Tiwary;Vivek R. Narasayya

  • Self-Tuning Technology in Microsoft SQL Server.

    Surajit Chaudhuri;Eric Christensen;Goetz Graefe;Vivek R. Narasayya

  • Database monitoring system

    Surajit Chaudhuri;Arnd Christian Konig;Vivek Narasayya

  • Estimating progress of execution for SQL queries

    Surajit Chaudhuri;Vivek Narasayya;Ravishankar Ramamurthy

  • Selectivity estimation for range predicates using lightweight models

    Anshuman Dutt;Chi Wang;Azade Nazi;Srikanth Kandula

  • A robust, optimization-based approach for approximate answering of aggregate queries

    Surajit Chaudhuri;Gautam Das;Vivek Narasayya

Frequent Co-Authors

Surajit Chaudhuri
Surajit Chaudhuri Microsoft (United States)
Kaushik Chakrabarti
Kaushik Chakrabarti Microsoft (United States)
Rajeev Motwani
Rajeev Motwani Stanford University
Feng Li
Feng Li Shandong University
Nicolas Bruno
Nicolas Bruno Microsoft (United States)
Gautam Das
Gautam Das The University of Texas at Arlington
Henry M. Levy
Henry M. Levy University of Washington
Arvind Arasu
Arvind Arasu Microsoft (United States)
Bolin Ding
Bolin Ding Alibaba Group (United States)
Sunita Sarawagi
Sunita Sarawagi Indian Institute of Technology Bombay

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