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Computer Science

D-Index
63
Citations
16515
World Ranking
2751
National Ranking
1368

Research.com Recognitions

  • 2019 - ACM Fellow For contributions to scalable distributed data systems

Overview

Magdalena Balazinska is affiliated with the University of Washington in the United States. Their research primarily spans the broad field of Computer Science with a focus on multiple subfields, including Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Information Systems, and Signal Processing.

Their work covers a variety of topics centered on machine learning and data analysis. Key research topics include Machine Learning and Data Classification, Multimodal Machine Learning Applications, Advanced Image and Video Retrieval Techniques, Human Pose and Action Recognition, Advanced Neural Network Applications, Explainable Artificial Intelligence (XAI), and Advanced Database Systems and Queries.

Magdalena Balazinska has contributed to numerous publications, particularly in well-known venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Proceedings of the VLDB Endowment
  • Proceedings of the ACM on Management of Data
  • ACM SIGMOD Record
  • Communications of the ACM

Recent notable papers by Magdalena Balazinska include:

  • Automated Detection of Glaucoma With Interpretable Machine Learning Using Clinical Data and Multimodal Retinal Images, 2021, American Journal of Ophthalmology
  • The Seattle Report on Database Research, 2020, ACM SIGMOD Record
  • The Seattle report on database research, 2022, Communications of the ACM
  • Automated detection of glaucoma with interpretable machine learning using clinical data and multi-modal retinal images, 2020, bioRxiv (Cold Spring Harbor Laboratory)
  • SafeBound: A Practical System for Generating Cardinality Bounds, 2023, Proceedings of the ACM on Management of Data

They have frequently collaborated with several co-authors, including Maureen Daum, Brandon Haynes, Dong He, Ranjay Krishna, and Dan Suciu, indicating ongoing partnerships in research projects.

In 2019, Magdalena Balazinska received the ACM Fellow award for contributions to scalable distributed data systems.

Best Publications

  • The Design of the Borealis Stream Processing Engine

    Daniel J. Abadi;Yanif Ahmad;Magdalena Balazinska;Mitch Cherniack

  • HaLoop: efficient iterative data processing on large clusters

    Yingyi Bu;Bill Howe;Magdalena Balazinska;Michael D. Ernst

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

    E. Welbourne;L. Battle;G. Cole;K. Gould

  • Scalable Distributed Stream Processing

    Mitch Cherniack;Hari Balakrishnan;Magdalena Balazinska;Don Carney

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

    Magdalena Balazinska;Paul Castro

  • SkewTune: mitigating skew in mapreduce applications

    YongChul Kwon;Magdalena Balazinska;Bill Howe;Jerome Rolia

  • High-availability algorithms for distributed stream processing

    J.-H. Hwang;M. Balazinska;A. Rasin;U. Cetintemel

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

    Magdalena Balazinska;Hari Balakrishnan;David Karger

  • Fault-tolerance in the Borealis distributed stream processing system

    Magdalena Balazinska;Hari Balakrishnan;Samuel Madden;Michael Stonebraker

  • Data Management in the Worldwide Sensor Web

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

  • Event queries on correlated probabilistic streams

    Christopher Ré;Julie Letchner;Magdalena Balazinksa;Dan Suciu

  • Advanced clone-analysis to support object-oriented system refactoring

    M. Balazinska;E. Merlo;M. Dagenais;B. Lague

  • ParaTimer: a progress indicator for MapReduce DAGs

    Kristi Morton;Magdalena Balazinska;Dan Grossman

  • A demonstration of SciDB: a science-oriented DBMS

    P. Cudre-Mauroux;H. Kimura;K.-T. Lim;J. Rogers

  • SnipSuggest: context-aware autocompletion for SQL

    Nodira Khoussainova;YongChul Kwon;Magdalena Balazinska;Dan Suciu

  • Infranet: Circumventing Web Censorship and Surveillance

    Nick Feamster;Magdalena Balazinska;Greg Harfst;Hari Balakrishnan

  • Measuring clone based reengineering opportunities

    M. Balazinska;E. Merlo;M. Dagenais;B. Lague

  • Skew-resistant parallel processing of feature-extracting scientific user-defined functions

    YongChul Kwon;Magdalena Balazinska;Bill Howe;Jerome Rolia

  • Query-Based Data Pricing

    Paraschos Koutris;Prasang Upadhyaya;Magdalena Balazinska;Bill Howe

  • Retrospective on Aurora

    Hari Balakrishnan;Magdalena Balazinska;Don Carney;Uğur Çetintemel

  • The HaLoop approach to large-scale iterative data analysis

    Yingyi Bu;Bill Howe;Magdalena Balazinska;Michael D. Ernst

Frequent Co-Authors

Dan Suciu
Dan Suciu University of Washington
Bill Howe
Bill Howe University of Washington
Alvin Cheung
Alvin Cheung University of California, Berkeley
Christopher Ré
Christopher Ré Stanford University
Gaetano Borriello
Gaetano Borriello University of Washington
Johannes Gehrke
Johannes Gehrke Microsoft (United States)
Dan Grossman
Dan Grossman University of Washington

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