H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 99 Citations 59,412 297 World Ranking 150 National Ranking 90

Research.com Recognitions

Awards & Achievements

2020 - ACM Fellow For contributions to data management and sensor computing systems

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Database
  • Programming language

His primary scientific interests are in Wireless sensor network, Database, Distributed computing, Real-time computing and Query optimization. His Wireless sensor network research incorporates themes from Data acquisition and Key distribution in wireless sensor networks, Wireless network. Database is frequently linked to Data science in his study.

His Distributed computing research focuses on subjects like Set, which are linked to Adaptive optimization and Response time. His Real-time computing research is multidisciplinary, incorporating perspectives in Simulation, Software deployment, Global Positioning System and Data visualization. His studies in Query optimization integrate themes in fields like Query language, Query expansion and Sargable.

His most cited work include:

  • TAG: a Tiny AGgregation service for Ad-Hoc sensor networks (2753 citations)
  • TinyDB: an acquisitional query processing system for sensor networks (1799 citations)
  • TinyOS: An Operating System for Sensor Networks (1111 citations)

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

His primary areas of study are Database, Wireless sensor network, Data mining, Distributed computing and Real-time computing. His Wireless sensor network study integrates concerns from other disciplines, such as Data acquisition, Key distribution in wireless sensor networks, Data management and Query optimization. Samuel Madden has researched Query optimization in several fields, including Query expansion and Sargable.

His Data mining research focuses on Set and how it relates to Massively parallel. Real-time computing is closely attributed to Global Positioning System in his study. His Computer network study combines topics in areas such as Wireless and Wireless network.

He most often published in these fields:

  • Database (24.23%)
  • Wireless sensor network (15.64%)
  • Data mining (14.11%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (8.59%)
  • Analytics (6.44%)
  • Data mining (14.11%)

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

Samuel Madden spends much of his time researching Artificial intelligence, Analytics, Data mining, Set and Information retrieval. His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning and Pattern recognition. The concepts of his Data mining study are interwoven with issues in Inverted index, Hash function and Global Positioning System.

Samuel Madden focuses mostly in the field of Key, narrowing it down to matters related to Snapshot and, in some cases, Distributed computing. Samuel Madden combines topics linked to Database with his work on Bandwidth. Particularly relevant to Replication is his body of work in Database.

Between 2018 and 2021, his most popular works were:

  • SageDB: A Learned Database System (74 citations)
  • Raha: A Configuration-Free Error Detection System (20 citations)
  • MLSys: The New Frontier of Machine Learning Systems (15 citations)

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

  • Operating system
  • Database
  • Programming language

His primary areas of investigation include Artificial intelligence, Set, Data mining, Process and Debugger. His Artificial intelligence research includes elements of Machine learning, Software system, Software deployment and Natural language processing. His study looks at the relationship between Set and fields such as Analytics, as well as how they intersect with chemical problems.

Many of his studies on Data mining apply to Contrast as well. Samuel Madden focuses mostly in the field of Process, narrowing it down to topics relating to Object detection and, in certain cases, Component, Key, Real-time computing and Baseline. The study incorporates disciplines such as Visualization, Workflow and Code in addition to Debugger.

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.

Best Publications

TAG: a Tiny AGgregation service for Ad-Hoc sensor networks

Samuel Madden;Michael J. Franklin;Joseph M. Hellerstein;Wei Hong.
operating systems design and implementation (2002)

4152 Citations

TinyDB: an acquisitional query processing system for sensor networks

Samuel R. Madden;Michael J. Franklin;Joseph M. Hellerstein;Wei Hong.
international conference on management of data (2005)

2573 Citations

TinyOS: An Operating System for Sensor Networks

Philip Levis;Samuel Madden;Joseph Polastre;Robert Szewczyk.
ambient intelligence (2005)

2141 Citations

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

A comparison of approaches to large-scale data analysis

Andrew Pavlo;Erik Paulson;Alexander Rasin;Daniel J. Abadi.
international conference on management of data (2009)

1474 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

CarTel: a distributed mobile sensor computing system

Bret Hull;Vladimir Bychkovsky;Yang Zhang;Kevin Chen.
international conference on embedded networked sensor systems (2006)

1397 Citations

C-store: a column-oriented DBMS

Mike Stonebraker;Daniel J. Abadi;Adam Batkin;Xuedong Chen.
very large data bases (2005)

1352 Citations

The design of an acquisitional query processor for sensor networks

Samuel Madden;Michael J. Franklin;Joseph M. Hellerstein;Wei Hong.
international conference on management of data (2003)

1345 Citations

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Best Scientists Citing Samuel Madden

Michael J. Franklin

Michael J. Franklin

University of Chicago

Publications: 85

Lei Chen

Lei Chen

Hong Kong University of Science and Technology

Publications: 81

Wolfgang Lehner

Wolfgang Lehner

TU Dresden

Publications: 80

Tarek Abdelzaher

Tarek Abdelzaher

University of Illinois at Urbana-Champaign

Publications: 78

Beng Chin Ooi

Beng Chin Ooi

National University of Singapore

Publications: 67

Joseph M. Hellerstein

Joseph M. Hellerstein

University of California, Berkeley

Publications: 66

Tim Kraska

Tim Kraska

MIT

Publications: 66

Magdalena Balazinska

Magdalena Balazinska

University of Washington

Publications: 62

Amol Deshpande

Amol Deshpande

University of Maryland, College Park

Publications: 62

Anastasia Ailamaki

Anastasia Ailamaki

École Polytechnique Fédérale de Lausanne

Publications: 60

Michael Stonebraker

Michael Stonebraker

MIT

Publications: 59

Jianzhong Li

Jianzhong Li

Harbin Institute of Technology

Publications: 59

Elke A. Rundensteiner

Elke A. Rundensteiner

Worcester Polytechnic Institute

Publications: 58

Panos K. Chrysanthis

Panos K. Chrysanthis

University of Pittsburgh

Publications: 57

Alfons Kemper

Alfons Kemper

Technical University of Munich

Publications: 56

Ion Stoica

Ion Stoica

University of California, Berkeley

Publications: 55

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