D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 56 Citations 14,984 140 World Ranking 2083 National Ranking 1136

Research.com Recognitions

Awards & Achievements

2019 - ACM Fellow For contributions to scalable distributed data systems

Overview

What is she best known for?

The fields of study she is best known for:

  • Operating system
  • Database
  • Programming language

Her primary areas of study are Distributed computing, Stream processing, Scalability, The Internet and World Wide Web. Her Distributed computing research includes themes of Theoretical computer science, Class, Directed acyclic graph, Node and Key. Magdalena Balazinska interconnects Fault tolerance, High availability, Set and Data stream management system in the investigation of issues within Stream processing.

In her study, Cache and Very large database is inextricably linked to Task, which falls within the broad field of Scalability. Her work on Web navigation as part of general The Internet research is frequently linked to Web application security, thereby connecting diverse disciplines of science. Her World Wide Web study incorporates themes from Control and Software deployment.

Her most cited work include:

  • The Design of the Borealis Stream Processing Engine (1264 citations)
  • HaLoop: efficient iterative data processing on large clusters (651 citations)
  • Building the Internet of Things Using RFID: The RFID Ecosystem Experience (535 citations)

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

Her main research concerns Data mining, Database, Data management, Distributed computing and Data science. Her Data mining research is multidisciplinary, incorporating perspectives in Event, Probabilistic logic, Theoretical computer science and Search engine indexing. Her work carried out in the field of Data management brings together such families of science as Sensor web, Wireless sensor network and World Wide Web.

Her Distributed computing research is multidisciplinary, relying on both Skew, Scalability and Cloud computing. The study incorporates disciplines such as Computer architecture, Data stream mining, Data processing and Relational database in addition to Scalability. Magdalena Balazinska has included themes like High availability and Set in her Stream processing study.

She most often published in these fields:

  • Data mining (17.42%)
  • Database (16.85%)
  • Data management (15.73%)

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

  • Artificial intelligence (8.99%)
  • Analytics (12.36%)
  • Sampling (3.37%)

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

Artificial intelligence, Analytics, Sampling, Machine learning and Database are her primary areas of study. Her Analytics study combines topics from a wide range of disciplines, such as Cloud data, Cloud computing, Codec and World Wide Web. Her work in Cloud data addresses subjects such as Provisioning, which are connected to disciplines such as Distributed computing.

Her Distributed computing research includes elements of Telecommunications network, Overhead and Data stream management system. Her biological study spans a wide range of topics, including Stream processing, Orientation, Computer graphics and Virtual reality. She combines subjects such as Set and Data management with her study of Clustering high-dimensional data.

Between 2016 and 2021, her most popular works were:

  • Learning State Representations for Query Optimization with Deep Reinforcement Learning (68 citations)
  • The Myria Big Data Management and Analytics System and Cloud Services. (49 citations)
  • Comparative evaluation of big-data systems on scientific image analytics workloads (28 citations)

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

  • Operating system
  • Database
  • Programming language

Magdalena Balazinska spends much of her time researching Analytics, Query optimization, World Wide Web, Data science and Artificial intelligence. Her studies deal with areas such as Representation, State, Relational algebra and Reinforcement learning as well as Query optimization. Her work carried out in the field of World Wide Web brings together such families of science as Cloud data, Cloud computing, myria- and Big data management.

She combines subjects such as Use case, Image and Big data with her study of Data science. Her Artificial intelligence research incorporates elements of Cardinality, Machine learning and Estimation. Magdalena Balazinska works mostly in the field of Estimation, limiting it down to topics relating to Cardinality and, in certain cases, Parameterized complexity, Hash function and Foreign key.

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

The Design of the Borealis Stream Processing Engine

Daniel J. Abadi;Yanif Ahmad;Magdalena Balazinska;Mitch Cherniack.
conference on innovative data systems research (2005)

1976 Citations

HaLoop: efficient iterative data processing on large clusters

Yingyi Bu;Bill Howe;Magdalena Balazinska;Michael D. Ernst.
very large data bases (2010)

1142 Citations

Building the Internet of Things Using RFID: The RFID Ecosystem Experience

E. Welbourne;L. Battle;G. Cole;K. Gould.
IEEE Internet Computing (2009)

843 Citations

Scalable Distributed Stream Processing

Mitch Cherniack;Hari Balakrishnan;Magdalena Balazinska;Don Carney.
conference on innovative data systems research (2003)

789 Citations

Characterizing mobility and network usage in a corporate wireless local-area network

Magdalena Balazinska;Paul Castro.
international conference on mobile systems, applications, and services (2003)

683 Citations

SkewTune: mitigating skew in mapreduce applications

YongChul Kwon;Magdalena Balazinska;Bill Howe;Jerome Rolia.
international conference on management of data (2012)

551 Citations

INS/Twine: A Scalable Peer-to-Peer Architecture for Intentional Resource Discovery

Magdalena Balazinska;Hari Balakrishnan;David Karger.
international conference on pervasive computing (2002)

407 Citations

High-availability algorithms for distributed stream processing

J.-H. Hwang;M. Balazinska;A. Rasin;U. Cetintemel.
international conference on data engineering (2005)

393 Citations

Fault-tolerance in the Borealis distributed stream processing system

Magdalena Balazinska;Hari Balakrishnan;Samuel R. Madden;Michael Stonebraker.
international conference on management of data (2005)

268 Citations

Advanced clone-analysis to support object-oriented system refactoring

M. Balazinska;E. Merlo;M. Dagenais;B. Lague.
working conference on reverse engineering (2000)

259 Citations

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

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