Chaofan Tao

About

Chaofan Tao is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Chaofan Tao has authored 10 papers receiving a total of 116 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 1 paper in Electrical and Electronic Engineering. Recurrent topics in Chaofan Tao’s work include Domain Adaptation and Few-Shot Learning (4 papers), Advanced Neural Network Applications (3 papers) and Multimodal Machine Learning Applications (2 papers). Chaofan Tao is often cited by papers focused on Domain Adaptation and Few-Shot Learning (4 papers), Advanced Neural Network Applications (3 papers) and Multimodal Machine Learning Applications (2 papers). Chaofan Tao collaborates with scholars based in Hong Kong, China and Sweden. Chaofan Tao's co-authors include Joseph Y. Lo, Cynthia Rudin, Chaofan Chen, Alina Jade Barnett, Fides R. Schwartz, Lifeng Shang, Ngai Wong, Ping Luo, Qun Liu and Lu Hou and has published in prestigious journals such as Pattern Recognition, IEEE Transactions on Neural Networks and Learning Systems and IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

In The Last Decade

Co-authorship network of co-authors of Chaofan Tao i

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Fields of papers citing papers by Chaofan Tao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Chaofan Tao

Since Specialization

Citations

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