Cameron Musco

30 papers and 440 indexed citations i.

About

Cameron Musco is a scholar working on Artificial Intelligence, Computational Mechanics and Computational Theory and Mathematics. According to data from OpenAlex, Cameron Musco has authored 30 papers receiving a total of 440 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 16 papers in Computational Mechanics and 9 papers in Computational Theory and Mathematics. Recurrent topics in Cameron Musco’s work include Sparse and Compressive Sensing Techniques (15 papers), Stochastic Gradient Optimization Techniques (13 papers) and Complex Network Analysis Techniques (6 papers). Cameron Musco is often cited by papers focused on Sparse and Compressive Sensing Techniques (15 papers), Stochastic Gradient Optimization Techniques (13 papers) and Complex Network Analysis Techniques (6 papers). Cameron Musco collaborates with scholars based in United States, Israel and Switzerland. Cameron Musco's co-authors include Christopher Musco, Michael B. Cohen, Charalampos E. Tsourakakis, Yin Tat Lee, Aaron Sidford, David P. Woodruff, Michael Kapralov, Richard Peng, Nancy Lynch and Hsin-Hao Su and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SIAM Journal on Matrix Analysis and Applications and Theory of Computing.

In The Last Decade

Co-authorship network of co-authors of Cameron Musco i

Fields of papers citing papers by Cameron Musco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cameron Musco. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Cameron Musco. The network helps show where Cameron Musco may publish in the future.

Countries citing papers authored by Cameron Musco

Since Specialization
Citations

This map shows the geographic impact of Cameron Musco's research. 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 Cameron Musco with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cameron Musco 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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