World's Best Scientists 2026 revealed!
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Computer Science
UK
2025

D-Index & Metrics

Computer Science

D-Index
75
Citations
27786
World Ranking
1392
National Ranking
81

Research.com Recognitions

  • 2025 - Research.com Computer Science in United Kingdom Leader Award
  • 2023 - Research.com Computer Science in United Kingdom Leader Award
  • 2022 - Research.com Computer Science in United Kingdom Leader Award
  • 2020 - ACM Fellow For contributions to data summarization and privacy enabling data management and analysis
  • 2013 - ACM Distinguished Member

Overview

Graham Cormode is affiliated with the University of Warwick in the United Kingdom. Their research primarily spans the field of Computer Science, with a focus on several subfields including Artificial Intelligence, Computer Networks and Communications, Signal Processing, Management Science and Operations Research, and Sociology and Political Science.

Their work covers a range of topics, notably:

  • Privacy-Preserving Technologies in Data
  • Cryptography and Data Security
  • Data Management and Algorithms
  • Stochastic Gradient Optimization Techniques
  • Data Quality and Management
  • Internet Traffic Analysis and Secure E-voting
  • Advanced Database Systems and Queries

Cormode has contributed to numerous publications, with recent papers including:

  • "Frequency estimation under local differential privacy," 2021, Proceedings of the VLDB Endowment
  • "Correlation Clustering in Data Streams," 2021, Algorithmica
  • "Federated Boosted Decision Trees with Differential Privacy," 2022, Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
  • "Opacus: User-Friendly Differential Privacy Library in PyTorch," 2021, arXiv (Cornell University)

In addition to articles, Cormode has published a book titled "Small Summaries for Big Data" in 2020 under Cambridge University Press.

Frequent co-authors in their research include:

  • Carsten Maple
  • Ke Yi
  • Samuel Maddock
  • Akash Bharadwaj
  • Pavel Veselý

Cormode often publishes in venues such as:

  • arXiv (Cornell University)
  • ACM SIGMOD Record
  • Proceedings of the VLDB Endowment
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Proceedings of the ACM on Management of Data

Recognition of their work includes awards such as the ACM Fellow in 2020, awarded for contributions to data summarization and privacy enabling data management and analysis, and the ACM Distinguished Member status received in 2013.

Best Publications

  • Advances and Open Problems in Federated Learning

    Peter Kairouz;H. Brendan McMahan;Brendan Avent;Aurélien Bellet

  • An improved data stream summary: the count-min sketch and its applications

    Graham Cormode;S. Muthukrishnan

  • Key differences between Web 1.0 and Web 2.0

    Graham Cormode;Balachander Krishnamurthy

  • Advances and open problems in federated learning

    Peter Kairouz;H. Brendan McMahan;Brendan Avent;Aurélien Bellet

  • What's hot and what's not: tracking most frequent items dynamically

    Graham Cormode;S. Muthukrishnan

  • Node Classification in Social Networks

    Smriti Bhagat;Graham Cormode;S. Muthukrishnan

  • Synopses for Massive Data: Samples, Histograms, Wavelets, Sketches

    Graham Cormode;Minos Garofalakis;Peter J. Haas;Chris Jermaine

  • Differentially Private Spatial Decompositions

    Graham Cormode;Cecilia Procopiuc;Divesh Srivastava;Entong Shen

  • PrivBayes: private data release via bayesian networks

    Jun Zhang;Graham Cormode;Cecilia M. Procopiuc;Divesh Srivastava

  • Finding frequent items in data streams

    Graham Cormode;Marios Hadjieleftheriou

  • What's hot and what's not: tracking most frequent items dynamically

    Unknown

  • An improved data stream summary: The count-min sketch and its applications

    Graham Cormode;S. Muthukrishnan

  • PrivBayes

    Unknown

  • The string edit distance matching problem with moves

    Graham Cormode;S. Muthukrishnan

  • What's new: finding significant differences in network data streams

    Graham Cormode;S. Muthukrishnan

  • Class-based graph anonymization for social network data

    Smriti Bhagat;Graham Cormode;Balachander Krishnamurthy;Divesh Srivastava

  • Sketching streams through the net: distributed approximate query tracking

    Graham Cormode;Minos Garofalakis

  • Holistic aggregates in a networked world: distributed tracking of approximate quantiles

    Graham Cormode;Minos Garofalakis;S. Muthukrishnan;Rajeev Rastogi

  • Practical verified computation with streaming interactive proofs

    Graham Cormode;Michael Mitzenmacher;Justin Thaler

  • Combinatorial algorithms for compressed sensing

    Graham Cormode;S. Muthukrishnan

  • Finding hierarchical heavy hitters in data streams

    Graham Cormode;Flip Korn;S. Muthukrishnan;Divesh Srivastava

  • Key Differences between Web1.0 and Web2.0

    Graham Cormode;Balachander Krishnamurthy

Frequent Co-Authors

Subbaratnam Muthukrishnan
Subbaratnam Muthukrishnan Kansas State University
Divesh Srivastava
Divesh Srivastava AT&T (United States)
Andrew McGregor
Andrew McGregor University of Massachusetts Amherst
Minos Garofalakis
Minos Garofalakis Technical University of Crete
Ke Yi
Ke Yi Hong Kong University of Science and Technology
Flip Korn
Flip Korn Google (United States)
Balachander Krishnamurthy
Balachander Krishnamurthy AT&T (United States)
Nick Duffield
Nick Duffield Texas A&M University
Ting Yu
Ting Yu Mohamed bin Zayed University of Artificial Intelligence

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