Machel Reid

About

Machel Reid is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Industrial relations. According to data from OpenAlex, Machel Reid has authored 9 papers receiving a total of 33 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 0 papers in Industrial relations. Recurrent topics in Machel Reid’s work include Natural Language Processing Techniques (9 papers), Topic Modeling (9 papers) and Text Readability and Simplification (3 papers). Machel Reid is often cited by papers focused on Natural Language Processing Techniques (9 papers), Topic Modeling (9 papers) and Text Readability and Simplification (3 papers). Machel Reid collaborates with scholars based in Japan and United States. Machel Reid's co-authors include Graham Neubig, Mikel Artetxe, Edison Marrese-Taylor, Yutaka Matsuo, Suchin Gururangan, Francesco Piccinno, Victor W. Zhong, Jonas Pfeiffer, Junjie Hu and Sebastian Ruder and has published in prestigious journals such as arXiv (Cornell University), Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Co-authorship network of co-authors of Machel Reid i

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Fields of papers citing papers by Machel Reid

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Machel Reid

Since Specialization

Citations

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