Computing in Science and Engineering

Top Research Topics at Computing in Science and Engineering?

Computing in Science and Engineering aims to foster the development of research in Data science, Computational science, Software, Supercomputer and Programming language. The work tackled in Computing in Science and Engineering goes beyond the discipline of Data science as it also encompasses Data visualization. Research on Software addressed in the journal frequently intersections with the field of Software engineering.

The study on Programming language featured in it expounds on the topic of Python (programming language) in particular.

• Data science (10.03%)
• Computational science (9.56%)
• Software (8.75%)

What are the most cited papers published in the journal?

• Matplotlib: A 2D Graphics Environment (14239 citations)
• The NumPy Array: A Structure for Efficient Numerical Computation (7056 citations)
• Python for Scientific Computing (1507 citations)

Research areas of the most cited articles at Computing in Science and Engineering:

The published papers aim to foster the development of research in Computational science, Supercomputer, Data science, Theoretical computer science and The Internet. The most cited papers explore issues in Computational science which can be linked to other research areas like Python (programming language), Finite element method, Parallel computing, Multigrid method and High-level programming language. The journal papers focus on Python (programming language) but the discussions also offer insight into other areas such as Computer graphics (images) and Scripting language.

What topics the last edition of the journal is best known for?

• Quantum mechanics
• Artificial intelligence
• Operating system

The previous edition focused in particular on these issues:

Computing in Science and Engineering mostly deals with topics like Python (programming language), Supercomputer, Software, Data science and Pandemic. It facilitates discussions on Python (programming language) that incorporate concepts from other fields like Parallel computing, Computer graphics (images) and Code generation. Issues in Supercomputer were discussed, taking into consideration concepts from other disciplines like Domain (software engineering), Scalability and Interface (Java).

Software research featured in Computing in Science and Engineering incorporates concerns from various other topics such as Computer architecture and Software engineering. The concepts on Software engineering presented in it can also apply to other research fields, including Software portability, Documentation and Workflow. The research on Data science tackled can also make contributions to studies in the areas of Visual analytics, Cloud computing, Data visualization and Focus (computing).

The most cited articles from the last journal are:

• Supercomputing Pipelines Search for Therapeutics Against COVID-19 (5 citations)
• Toward Long-Term and Archivable Reproducibility (4 citations)
• Accelerating Scientific Applications With SambaNova Reconfigurable Dataflow Architecture (4 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing in Computing in Science and Engineering (based on the number of publications) are:

• Charles Day (48 papers) absent at the last edition,
• Francis Sullivan (37 papers) absent at the last edition,
• George K. Thiruvathukal (33 papers) published 2 papers at the last edition, 1 more than at the previous edition,
• Isabel Beichl (27 papers) absent at the last edition,
• Dianne P. O'Leary (25 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Computing in Science and Engineering (based on the number of publications) are:

• Los Alamos National Laboratory (32 papers) published 4 papers at the last edition, 2 more than at the previous edition,
• University of Illinois at Urbana–Champaign (29 papers) published 4 papers at the last edition the same number as at the previous edition,
• Loyola University Chicago (29 papers) published 1 paper at the last edition the same number as at the previous edition,
• Argonne National Laboratory (27 papers) published 5 papers at the last edition, 3 more than at the previous edition,
• University of Maryland, College Park (27 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 12.50% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 25.40% were posted by at least one author from the top 10 institutions publishing in the journal. Another 9.52% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 23.81% of all publications and 41.27% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

How to Contribute to the Journal

If you are interested to contribute to Computing in Science and Engineering, there are several roles that you could consider. Whether you're a researcher in Data Science, Computational Science, or Software, your unique insights and studies will be valuable. For academics aspiring to kickstart their career in research publication, it would be helpful to bag some teaching experience. If you are interested to start as a preschool teacher in the state, you can read our guide on how to become a preschool teacher in New Jersey.

Furthermore, successful submissions usually contain original research, surveys, tutorials, and papers that express the personal viewpoint of the author. Contributions are welcome from researchers and professionals worldwide.

Once you are ready to contribute, make sure to review the submission guidelines to ensure that your research or article aligns with the standards of the journal. The review process could take several weeks, but rest assured that your work will be evaluated thoroughly to maintain the quality of publications.

Engaging with Computing in Science and Engineering as an author or researcher is an excellent choice for professionals seeking to advance their research and contribute to their fields. We look forward to reviewing your contributions and welcoming you to our research community.