James Fan

29 papers and 938 indexed citations i.

About

James Fan is a scholar working on Artificial Intelligence, Management Science and Operations Research and Safety Research. According to data from OpenAlex, James Fan has authored 29 papers receiving a total of 938 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 5 papers in Management Science and Operations Research and 3 papers in Safety Research. Recurrent topics in James Fan’s work include Topic Modeling (19 papers), Natural Language Processing Techniques (17 papers) and Semantic Web and Ontologies (8 papers). James Fan is often cited by papers focused on Topic Modeling (19 papers), Natural Language Processing Techniques (17 papers) and Semantic Web and Ontologies (8 papers). James Fan collaborates with scholars based in United States, Australia and Hong Kong. James Fan's co-authors include David Gondek, Aditya Kalyanpur, Jennifer Chu‐Carroll, David Ferrucci, Eric Nyberg, Nico Schlaefer, Chris Welty, J. William Murdock, John Prager and Eric W. Brown and has published in prestigious journals such as Production and Operations Management, Applied Spectroscopy and Manufacturing & Service Operations Management.

In The Last Decade

Co-authorship network of co-authors of James Fan i

Fields of papers citing papers by James Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by James Fan

Since Specialization
Citations

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