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D-Index & Metrics

Computer Science

D-Index
51
Citations
13773
World Ranking
5248
National Ranking
2417

Overview

Amol Deshpande is affiliated with the University of Maryland, College Park in the United States. Their research spans primarily the field of Computer Science, with a focus on several specialized subfields such as Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Signal Processing, and Electrical and Electronic Engineering.

Their work addresses multiple core topics, including Graph Theory and Algorithms, Data Management and Algorithms, Advanced Database Systems and Queries, Bluetooth and Wireless Communication Technologies, IoT-based Smart Home Systems, Mobile and Web Applications, and Digital Imaging for Blood Diseases.

Deshpande has contributed to a variety of research publications over recent years. Notable papers include:

  • "Modern Techniques For Querying Graph-structured Databases," 2024, Foundations and Trends in Databases
  • "Bluetooth Based Electronic Notice Board," 2020, International Journal of Engineering and Advanced Technology
  • "Early Stage Detection of Multiple Sclerosis using FCNN," 2022, 2022 10th International Conference on Emerging Trends in Engineering and Technology - Signal and Information Processing (ICETET-SIP-22)
  • "Comprehending C codes with LLMs: Effective comment generation through retrieval and reasoning," 2025, Pattern Recognition Letters
  • "To Store or Not to Store: a graph theoretical approach for Dataset Versioning," 2024, arXiv (Cornell University)

Frequent collaborators in their work include Amine Mhedhbi, Semih Salihoğlu, Ashutosh Pandya, Chinmay Raut, and Mihir Patel. The recurring publication venues for Deshpande feature journals and conferences such as arXiv (Cornell University), Foundations and Trends in Databases, International Journal of Engineering and Advanced Technology, ICETET-SIP-22 conference, and Pattern Recognition Letters.

Best Publications

  • TelegraphCQ: continuous dataflow processing

    Sirish Chandrasekaran;Owen Cooper;Amol Deshpande;Michael J. Franklin

  • TelegraphCQ: Continuous Dataflow Processing for an Uncertain World.

    Sirish Chandrasekaran;Owen Cooper;Amol Deshpande;Michael J. Franklin

  • Model-driven data acquisition in sensor networks

    Amol Deshpande;Carlos Guestrin;Samuel R. Madden;Joseph M. Hellerstein

  • Approximate Data Collection in Sensor Networks using Probabilistic Models

    D. Chu;A. Deshpande;J.M. Hellerstein;Wei Hong

  • Adaptive Query Processing

    Amol Deshpande;Zachary Ives;Vijayshankar Raman

  • Representing and Querying Correlated Tuples in Probabilistic Databases

    Prithviraj Sen;A. Deshpande

  • Adaptive Query Processing: Technology in Evolution.

    Joseph M. Hellerstein;Michael J. Franklin;Sirish Chandrasekaran;Amol Deshpande

  • MauveDB: supporting model-based user views in database systems

    Amol Deshpande;Samuel Madden

  • Data Management in the Worldwide Sensor Web

    M. Balazinska;A. Deshpande;M.J. Franklin;P.B. Gibbons

  • Cache-and-query for wide area sensor databases

    Amol Deshpande;Suman Nath;Phillip B. Gibbons;Srinivasan Seshan

  • Efficient snapshot retrieval over historical graph data

    U. Khurana;A. Deshpande

  • Independence is good: dependency-based histogram synopses for high-dimensional data

    Amol Deshpande;Minos Garofalakis;Rajeev Rastogi

  • Exploiting correlated attributes in acquisitional query processing

    Amol Deshpande;C. Guestrin;W. Hong;S. Madden

  • Online Filtering, Smoothing and Probabilistic Modeling of Streaming data

    B. Kanagal;A. Deshpande

  • Using state modules for adaptive query processing

    Vijayshankar Raman;A. Deshpande;J.M. Hellerstein

  • Model-based approximate querying in sensor networks

    Amol Deshpande;Carlos Guestrin;Samuel R. Madden;Joseph M. Hellerstein;Joseph M. Hellerstein

  • TelegraphCQ: An Architectural Status Report

    Sailesh Krishnamurthy;Sirish Chandrasekaran;Owen Cooper;Amol Deshpande

  • DataHub: Collaborative Data Science & Dataset Version Management at Scale

    Anant P. Bhardwaj;Souvik Bhattacherjee;Amit Chavan;Amol Deshpande

  • SWORD: scalable workload-aware data placement for transactional workloads

    Abdul Quamar;K. Ashwin Kumar;Amol Deshpande

  • A unified approach to ranking in probabilistic databases

    Jian Li;Barna Saha;Amol Deshpande

Frequent Co-Authors

Lise Getoor
Lise Getoor University of California, Santa Cruz
Joseph M. Hellerstein
Joseph M. Hellerstein University of California, Berkeley
Aditya Parameswaran
Aditya Parameswaran University of California, Berkeley
Suman Nath
Suman Nath Microsoft (United States)
Samir Khuller
Samir Khuller Northwestern University
Srinivasan Seshan
Srinivasan Seshan Carnegie Mellon University
Phillip B. Gibbons
Phillip B. Gibbons Carnegie Mellon University
Carlos Guestrin
Carlos Guestrin Stanford University
Vijayshankar Raman
Vijayshankar Raman Google (United States)

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