Computational Complexity

490 papers and 6.9k indexed citations i.

About

The 490 papers published in Computational Complexity in the last decades have received a total of 6.9k indexed citations. Papers published in Computational Complexity usually cover Computational Theory and Mathematics (426 papers), Artificial Intelligence (315 papers) and Computer Networks and Communications (50 papers) specifically the topics of Combinatorial Optimization and Complexity Theory (299 papers), Cryptography and Data Security (118 papers) and Advanced Graph Theory Research (96 papers). The most active scholars publishing in Computational Complexity are Noam Nisan, Lance Fortnow, László Babai, Carsten Lund, Russell Impagliazzo, Avi Wigderson, Ran Raz, Richard Beigel, Alexander Razborov and Emanuele Viola.

In The Last Decade

Fields of papers published in Computational Complexity

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Computational Complexity. 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 Computational Complexity.

Countries where authors publish in Computational Complexity

Since Specialization
Citations

This map shows the geographic impact of research published in Computational Complexity. 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 Computational Complexity with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Computational Complexity more than expected).

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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