Christopher Musco

29 papers and 473 indexed citations i.

About

Christopher Musco is a scholar working on Artificial Intelligence, Computational Mechanics and Computational Theory and Mathematics. According to data from OpenAlex, Christopher Musco has authored 29 papers receiving a total of 473 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 11 papers in Computational Mechanics and 9 papers in Computational Theory and Mathematics. Recurrent topics in Christopher Musco’s work include Stochastic Gradient Optimization Techniques (10 papers), Sparse and Compressive Sensing Techniques (10 papers) and Matrix Theory and Algorithms (5 papers). Christopher Musco is often cited by papers focused on Stochastic Gradient Optimization Techniques (10 papers), Sparse and Compressive Sensing Techniques (10 papers) and Matrix Theory and Algorithms (5 papers). Christopher Musco collaborates with scholars based in United States, Israel and Switzerland. Christopher Musco's co-authors include Cameron Musco, Michael B. Cohen, Charalampos E. Tsourakakis, Yin Tat Lee, Aaron Sidford, Michael Kapralov, Richard Peng, David P. Woodruff, Juliana Freire and Martin Rinard and has published in prestigious journals such as Proceedings of the VLDB Endowment, Computer Graphics Forum and SIAM Journal on Matrix Analysis and Applications.

In The Last Decade

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

Fields of papers citing papers by Christopher Musco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher 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 Christopher Musco. The network helps show where Christopher Musco may publish in the future.

Countries citing papers authored by Christopher Musco

Since Specialization
Citations

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