H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 46 Citations 12,700 116 World Ranking 3444 National Ranking 1784

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Database
  • Artificial intelligence

His primary areas of study are Data mining, Probabilistic logic, Wireless sensor network, Distributed computing and Query optimization. His Data mining research includes themes of Data modeling, Database and Set. His Probabilistic logic research incorporates themes from Probabilistic database, Graphical model, Machine learning and Optimization problem.

His Distributed computing research incorporates elements of Scalability, Cloud computing, Dataflow and Partition. His Query optimization research integrates issues from Query expansion and Theoretical computer science. His Query expansion study which covers Query language that intersects with Data stream mining.

His most cited work include:

  • TelegraphCQ: Continuous Dataflow Processing for an Uncertain World. (1083 citations)
  • Model-driven data acquisition in sensor networks (1028 citations)
  • TelegraphCQ: continuous dataflow processing (607 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of investigation include Data mining, Theoretical computer science, Query optimization, Database and Graph. His Data mining research includes elements of Tuple, Wireless sensor network, Inference, Graphical model and Probabilistic logic. His biological study spans a wide range of topics, including Probabilistic database, Machine learning, Uncertain data and Time complexity.

His work carried out in the field of Query optimization brings together such families of science as Query language, Query expansion, Data stream mining and Distributed computing. His Database research is multidisciplinary, incorporating elements of Information extraction and Markov chain. Amol Deshpande has included themes like Graph and Analytics in his Graph study.

He most often published in these fields:

  • Data mining (28.31%)
  • Theoretical computer science (25.30%)
  • Query optimization (18.67%)

What were the highlights of his more recent work (between 2016-2021)?

  • Data science (12.05%)
  • Data management (12.05%)
  • Theoretical computer science (25.30%)

In recent papers he was focusing on the following fields of study:

Amol Deshpande focuses on Data science, Data management, Theoretical computer science, Graph and Graph. Within one scientific family, Amol Deshpande focuses on topics pertaining to Metadata under Data science, and may sometimes address concerns connected to Query language, Approximation algorithm, Automatic summarization, Vertex and Segmentation. Data management is a subfield of Database that he studies.

The concepts of his Theoretical computer science study are interwoven with issues in Relational database, Data mining and Hash function. Amol Deshpande interconnects Crowdsourcing, Intersection, Query expansion and Leverage in the investigation of issues within Data mining. His research in Graph focuses on subjects like Data modeling, which are connected to RDF.

Between 2016 and 2021, his most popular works were:

  • Towards Unified Data and Lifecycle Management for Deep Learning (49 citations)
  • Big Graph Analytics Platforms (39 citations)
  • ModelHub: Deep Learning Lifecycle Management (37 citations)

In his most recent research, the most cited papers focused on:

  • Operating system
  • Artificial intelligence
  • Database

Amol Deshpande mostly deals with Application lifecycle management, Data management, Data science, Graph and Software engineering. His Data management study combines topics in areas such as Query expansion, Heuristics and Query optimization. The Graph study combines topics in areas such as Relational database, Analytics and Graph.

His research investigates the connection between Analytics and topics such as Relational database management system that intersect with issues in Theoretical computer science and Graph database. He has researched Artificial intelligence in several fields, including Data modeling, Machine learning, SQL and Domain-specific language. His Graph rewriting study frequently links to related topics such as Data mining.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

TelegraphCQ: continuous dataflow processing

Sirish Chandrasekaran;Owen Cooper;Amol Deshpande;Michael J. Franklin.
international conference on management of data (2003)

2116 Citations

TelegraphCQ: Continuous Dataflow Processing for an Uncertain World.

Sirish Chandrasekaran;Owen Cooper;Amol Deshpande;Michael J. Franklin.
conference on innovative data systems research (2003)

1726 Citations

Model-driven data acquisition in sensor networks

Amol Deshpande;Carlos Guestrin;Samuel R. Madden;Joseph M. Hellerstein.
very large data bases (2004)

1471 Citations

Approximate Data Collection in Sensor Networks using Probabilistic Models

D. Chu;A. Deshpande;J.M. Hellerstein;Wei Hong.
international conference on data engineering (2006)

607 Citations

Adaptive Query Processing

Amol Deshpande;Zachary Ives;Vijayshankar Raman.
(2007)

411 Citations

Representing and Querying Correlated Tuples in Probabilistic Databases

Prithviraj Sen;A. Deshpande.
international conference on data engineering (2007)

314 Citations

Adaptive Query Processing: Technology in Evolution.

Joseph M. Hellerstein;Michael J. Franklin;Sirish Chandrasekaran;Amol Deshpande.
IEEE Data(base) Engineering Bulletin (2000)

309 Citations

MauveDB: supporting model-based user views in database systems

Amol Deshpande;Samuel Madden.
international conference on management of data (2006)

272 Citations

Data Management in the Worldwide Sensor Web

M. Balazinska;A. Deshpande;M.J. Franklin;P.B. Gibbons.
IEEE Pervasive Computing (2007)

248 Citations

Cache-and-query for wide area sensor databases

Amol Deshpande;Suman Nath;Phillip B. Gibbons;Srinivasan Seshan.
international conference on management of data (2003)

206 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

If you think any of the details on this page are incorrect, let us know.

Contact us

Top Scientists Citing Amol Deshpande

Dan Suciu

Dan Suciu

University of Washington

Publications: 55

Michael J. Franklin

Michael J. Franklin

University of Chicago

Publications: 47

Christopher Ré

Christopher Ré

Stanford University

Publications: 46

Joseph M. Hellerstein

Joseph M. Hellerstein

University of California, Berkeley

Publications: 45

Anand Srinivasan

Anand Srinivasan

Business International Corporation

Publications: 44

Samuel Madden

Samuel Madden

MIT

Publications: 42

Magdalena Balazinska

Magdalena Balazinska

University of Washington

Publications: 41

Jennifer Widom

Jennifer Widom

Stanford University

Publications: 39

Bugra Gedik

Bugra Gedik

Facebook (United States)

Publications: 38

Reynold Cheng

Reynold Cheng

University of Hong Kong

Publications: 37

Minos Garofalakis

Minos Garofalakis

Technical University of Crete

Publications: 37

Elke A. Rundensteiner

Elke A. Rundensteiner

Worcester Polytechnic Institute

Publications: 35

Kun-Lung Wu

Kun-Lung Wu

IBM (United States)

Publications: 33

Lei Chen

Lei Chen

Hong Kong University of Science and Technology

Publications: 33

Michael Stonebraker

Michael Stonebraker

MIT

Publications: 32

Something went wrong. Please try again later.