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IEEE

IEEE Symposium on Foundations of Computer Science (FOCS)

Location: Denver , United States

Submission deadline: 4/4/2022

Conference dates: 10/31/2022 - 11/3/2022

Research H-index
30

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 61 152 229 30

Call for Papers

Papers presenting new and original research on theory of computation are sought. Typical but not exclusive topics of interest include: algorithms and data structures, computational complexity, cryptography, computational learning theory, computational game theory, foundations of machine learning, parallel and distributed algorithms, quantum computing, computational geometry, computational applications of logic, algorithmic graph theory and combinatorics, optimization, randomness in computing, approximation algorithms, algorithmic coding theory, algebraic computation, and theoretical aspects of areas such as networks, privacy, information retrieval, computational biology, and databases. Papers that broaden the reach of the theory of computing, or raise important problems that can benefit from theoretical investigation and analysis, are encouraged.

Overview

The ranking presented on this page features a comprehensive evaluation of scientific conferences within the field of Computer Science. Developed by Research.com—a leading authority in science research data across all major disciplines since 2014—this ranking aims to provide a trusted, transparent overview of conferences making the highest scientific impact in recent years.

Each conference’s position in the ranking is determined by a unique bibliometric score, a robust metric devised by Research.com. This score integrates both the estimated h-index of each conference and the number of eminent scientists who have contributed to it over the last three years. Impact Score values reflected here were meticulously gathered as of 2024-11-27.

The ranking process embodies a rigorous and sophisticated analytical approach. A total of more than 2,742 Computer Science conferences were scrutinized, selected through detailed inspection and rigorous examination of over 148,739 scientific documents published during the last three years. These documents were authored by 13,184 leading and respected scientists in the Computer Science community, ensuring that only conferences with significant and recent research contributions are included.

This systematic and expert-driven methodology ensures that the resulting ranking is both comprehensive and credible, providing valuable insight for researchers, institutions, and stakeholders seeking to identify premier conferences in the field. For a detailed overview of the methodology used in computing the ranking scores, please refer to the Methodology Page.

Papers citation over time

A key indicator for each conference 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.

The top authors publishing at Foundations of Computer Science (based on the number of publications) are:

  • Avi Wigderson (47 papers) published 1 paper at the last edition, 1 less than at the previous edition,
  • Noga Alon (43 papers) absent at the last edition,
  • Christos H. Papadimitriou (38 papers) absent at the last edition,
  • Baruch Awerbuch (36 papers) absent at the last edition,
  • Oded Goldreich (32 papers) absent at the last edition.

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

Only papers with recognized affiliations are considered

The top affiliations publishing at Foundations of Computer Science (based on the number of publications) are:

  • Massachusetts Institute of Technology (307 papers) published 15 papers at the last edition, 6 more than at the previous edition,
  • University of California, Berkeley (181 papers) published 13 papers at the last edition, 7 more than at the previous edition,
  • Tel Aviv University (159 papers) published 6 papers at the last edition, 3 less than at the previous edition,
  • Princeton University (154 papers) published 11 papers at the last edition, 5 more than at the previous edition,
  • Microsoft (151 papers) published 5 papers at the last edition, 1 more than at the previous edition.

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

Publication chance based on affiliation

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

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 2020 edition, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 44.68% were posted by at least one author from the top 10 institutions publishing at the conference. Another 15.60% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 17.73% of all publications and 21.99% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference 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 conference 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 at a conference. The index includes the authors publishing at the last edition of a conference, 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.

Related Online Degrees & Career Pathways

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Beyond degrees, targeted courses and certifications are essential for career growth. For example, cybersecurity courses with certificates provide focused training in a critical tech field. Similarly, emerging roles such as AI trainers require understanding both machine learning and human interaction, detailed in resources about ai training jobs.

By combining relevant online degrees with targeted certifications, students and professionals can build robust career pathways and stay competitive in the evolving technology landscape.

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