Jeff Da

3 papers and 173 indexed citations i.

About

Jeff Da is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Social Psychology. According to data from OpenAlex, Jeff Da has authored 3 papers receiving a total of 173 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 1 paper in Computer Vision and Pattern Recognition and 1 paper in Social Psychology. Recurrent topics in Jeff Da’s work include Natural Language Processing Techniques (2 papers), Topic Modeling (2 papers) and Multimodal Machine Learning Applications (1 paper). Jeff Da is often cited by papers focused on Natural Language Processing Techniques (2 papers), Topic Modeling (2 papers) and Multimodal Machine Learning Applications (1 paper). Jeff Da collaborates with scholars based in United States. Jeff Da's co-authors include Yejin Choi, Jena D. Hwang, Antoine Bosselut, Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, Aslı Çelikyılmaz, Saadia Gabriel, Ari Holtzman and Jan Buys and has published in prestigious journals such as arXiv (Cornell University) and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Co-authorship network of co-authors of Jeff Da i

Fields of papers citing papers by Jeff Da

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Jeff Da

Since Specialization
Citations

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