Computing in Science & Engineering

84k citations
1.7k papers · · active since 1999

Impact in

    • Galaxies: Formation, Evolution, Phenomena
    • Stellar, planetary, and galactic studies
    • Astrophysics and Star Formation Studies
    • Pulsars and Gravitational Waves Research
    • Gamma-ray bursts and supernovae
    • Parallel Computing and Optimization Techniques

Papers in

Computing in Science & Engineering

1.5k papers receiving 80.5k citations

Peers

Computing in Science & Engineering
Comparison fields: 5 of 243
  • Astronomy and Astrophysics 20.8k
  • Hardware and Architecture 4.5k
  • Information Systems and Management 3.3k
  • Instrumentation 716
  • Computer Graphics and Computer-Aided Design 832
Replace Journal of the Royal Statistical Society Series B (Statistical Methodology) with:
Journal of the Royal Statistical Society Series B (Statistical Methodology) United States
Reviews of Modern Physics United States
SIAM Review United States
IEEE Signal Processing Magazine United States
Neural Computation United States
IBM Journal of Research and Development United States
Bell System Technical Journal United States
Physics Reports United States
Machine Learning United States
ACM Transactions on Mathematical Software United States
Computing in Science & Engineering relative to Journal of the Royal Statistical Society Series B (Statistical Methodology) United States Journal of the Royal Statistical Society Series B (Statistical Methodology)'s profile →
Citations per field
00.5×5×11.2×
Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1×
Citations per year

Countries where authors publish in Computing in Science & Engineering

Since Specialization
Citations

This map shows the geographic impact of research published in Computing in Science & Engineering. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers published in Computing in Science & Engineering with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Computing in Science & Engineering more than expected).

Fields of papers published in Computing in Science & Engineering

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Computing in Science & Engineering. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Computing in Science & Engineering.

About Computing in Science & Engineering

The 1.7k papers published in Computing in Science & Engineering in the last decades have received a total of 84k indexed citations . Papers published in Computing in Science & Engineering usually cover Hardware and Architecture (272 papers), Information Systems and Management (285 papers), Computer Graphics and Computer-Aided Design (99 papers), Computer Science Applications (101 papers) and Modeling and Simulation (43 papers) specifically the topics of Scientific Computing and Data Management (263 papers), Parallel Computing and Optimization Techniques (248 papers), Distributed and Parallel Computing Systems (137 papers), Computer Graphics and Visualization Techniques (91 papers), Data Visualization and Analytics (70 papers), Software Engineering Techniques and Practices (68 papers), Teaching and Learning Programming (59 papers) and Computational Physics and Python Applications (58 papers). The most active scholars publishing in Computing in Science & Engineering are John D. Hunter, Gael P. Varoquaux, Stéfan van der Walt, Travis E. Oliphant, Brian Granger, Fernando Pérez, David Paul Landau, Frank McKenna, Dietrich Braess and Karsten W. Jacobsen.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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