John DeNero

29 papers and 640 indexed citations i.

About

John DeNero is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, John DeNero has authored 29 papers receiving a total of 640 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Molecular Biology. Recurrent topics in John DeNero’s work include Topic Modeling (27 papers), Natural Language Processing Techniques (25 papers) and Multimodal Machine Learning Applications (5 papers). John DeNero is often cited by papers focused on Topic Modeling (27 papers), Natural Language Processing Techniques (25 papers) and Multimodal Machine Learning Applications (5 papers). John DeNero collaborates with scholars based in United States. John DeNero's co-authors include Dan Klein, Alexandre Bouchard‐Côté, Taylor Berg-Kirkpatrick, Greg Durrett, Joern Wuebker, Spence Green, Jakob Uszkoreit, Aria Haghighi, John Blitzer and Rohan Chitnis and has published in prestigious journals such as Journal of Biomedical Informatics, JMIR Research Protocols and JAMIA Open.

In The Last Decade

Co-authorship network of co-authors of John DeNero i

Fields of papers citing papers by John DeNero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by John DeNero

Since Specialization
Citations

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