Yi Dai

About

Yi Dai is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yi Dai has authored 25 papers receiving a total of 85 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Information Systems and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Yi Dai’s work include Topic Modeling (3 papers), Multimodal Machine Learning Applications (2 papers) and Mental Health via Writing (2 papers). Yi Dai is often cited by papers focused on Topic Modeling (3 papers), Multimodal Machine Learning Applications (2 papers) and Mental Health via Writing (2 papers). Yi Dai collaborates with scholars based in China, United States and Japan. Yi Dai's co-authors include Shilu Zhang, Mingzhe Liu, Yang Luo, Ling Feng, Bin Dai, Zhengwei Fu, Yu Guang Wang, Qing Zhu, Yongbin Li and Hirosato Kanda and has published in prestigious journals such as Bioinformatics, Scientific Reports and Journal of Affective Disorders.

In The Last Decade

Co-authorship network of co-authors of Yi Dai i

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Fields of papers citing papers by Yi Dai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Yi Dai

Since Specialization

Citations

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