Cullen Schaffer

About

Cullen Schaffer is a scholar working on Artificial Intelligence, Information Systems and Molecular Biology. According to data from OpenAlex, Cullen Schaffer has authored 7 papers receiving a total of 636 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 3 papers in Information Systems and 2 papers in Molecular Biology. Recurrent topics in Cullen Schaffer’s work include Imbalanced Data Classification Techniques (4 papers), Machine Learning and Data Classification (4 papers) and Data Mining Algorithms and Applications (3 papers). Cullen Schaffer is often cited by papers focused on Imbalanced Data Classification Techniques (4 papers), Machine Learning and Data Classification (4 papers) and Data Mining Algorithms and Applications (3 papers). Cullen Schaffer collaborates with scholars based in United States. Cullen Schaffer's co-authors include and and has published in prestigious journals such as Machine Learning and National Conference on Artificial Intelligence.

In The Last Decade

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Fields of papers citing papers by Cullen Schaffer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Cullen Schaffer

Since Specialization

Citations

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