Xinyi Dai

109 total papers · 1.8k total citations
63 papers, 1.2k citations indexed

About

Xinyi Dai is a scholar working on Artificial Intelligence, Information Systems and Surgery. According to data from OpenAlex, Xinyi Dai has authored 63 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 14 papers in Information Systems and 11 papers in Surgery. Recurrent topics in Xinyi Dai's work include Recommender Systems and Techniques (14 papers), Advanced Graph Neural Networks (9 papers) and Topic Modeling (8 papers). Xinyi Dai is often cited by papers focused on Recommender Systems and Techniques (14 papers), Advanced Graph Neural Networks (9 papers) and Topic Modeling (8 papers). Xinyi Dai collaborates with scholars based in China, Germany and United States. Xinyi Dai's co-authors include Ruiming Tang, Weinan Zhang, Yong Yu, Arndt F. Schilling, Yi Shen, Huaiyuan Zheng, Haokun Chen, Wei Nie, Aldo R. Boccaccini and Kai Zheng and has published in prestigious journals such as Chemical Engineering Journal, ACS Applied Materials & Interfaces and Electrochimica Acta.

In The Last Decade

Xinyi Dai

59 papers receiving 1.1k citations

Hit Papers

How Can Recommender Syste... 2024 2026 2024 10 20 30 40

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Xinyi Dai 325 266 225 199 182 63 1.2k
Yejing Wang 119 0.4× 151 0.6× 199 0.9× 543 2.7× 45 0.2× 51 1.1k
Jiying Wang 164 0.5× 420 1.6× 94 0.4× 65 0.3× 138 0.8× 32 1.0k
Xiaoyi Ma 410 1.3× 90 0.3× 138 0.6× 85 0.4× 199 1.1× 51 1.1k
Xuan Zhou 73 0.2× 121 0.5× 115 0.5× 188 0.9× 37 0.2× 55 924
Shanfeng Wang 302 0.9× 211 0.8× 473 2.1× 207 1.0× 114 0.6× 71 1.5k
Chuang Hu 192 0.6× 99 0.4× 212 0.9× 70 0.4× 36 0.2× 72 1.0k
Huiyang Li 66 0.2× 54 0.2× 100 0.4× 40 0.2× 148 0.8× 54 1.0k
Nikhil Rao 311 1.0× 106 0.4× 261 1.2× 270 1.4× 335 1.8× 63 1.3k
Xiangjun Zhao 454 1.4× 22 0.1× 306 1.4× 297 1.5× 25 0.1× 59 1.4k
Vincenzo Riccio 300 0.9× 252 0.9× 211 0.9× 22 0.1× 240 1.3× 33 1.2k

Countries citing papers authored by Xinyi Dai

Since Specialization
Citations

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

Fields of papers citing papers by Xinyi Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xinyi Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Xinyi Dai. A scholar is included among the top collaborators of Xinyi Dai based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xinyi Dai. Xinyi Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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