Liuyi Yao

50 total papers · 1.2k total citations
26 papers, 636 citations indexed

About

Liuyi Yao is a scholar working on Artificial Intelligence, Statistics and Probability and Cognitive Neuroscience. According to data from OpenAlex, Liuyi Yao has authored 26 papers receiving a total of 636 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 7 papers in Statistics and Probability and 2 papers in Cognitive Neuroscience. Recurrent topics in Liuyi Yao's work include Advanced Causal Inference Techniques (7 papers), Privacy-Preserving Technologies in Data (6 papers) and Statistical Methods and Inference (5 papers). Liuyi Yao is often cited by papers focused on Advanced Causal Inference Techniques (7 papers), Privacy-Preserving Technologies in Data (6 papers) and Statistical Methods and Inference (5 papers). Liuyi Yao collaborates with scholars based in United States, China and Singapore. Liuyi Yao's co-authors include Yaliang Li, Aidong Zhang, Sheng Li, Jing Gao, Zhixuan Chu, Mengdi Huai, Bolin Ding, Jingren Zhou, Yuexiang Xie and Daoyuan Chen and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Knowledge and Data Engineering and Proceedings of the VLDB Endowment.

In The Last Decade

Liuyi Yao

23 papers receiving 621 citations

Hit Papers

A Survey on Causal Inference 2021 2026 2022 2024 2021 50 100 150 200 250

Author Peers

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

Author Last Decade Papers Cites
Liuyi Yao 374 108 94 50 47 26 636
David Mease 298 0.8× 60 0.6× 99 1.1× 37 0.7× 83 1.8× 15 648
Jiji Zhang 510 1.4× 114 1.1× 79 0.8× 95 1.9× 14 0.3× 50 703
Carlos J. Mantas 511 1.4× 50 0.5× 137 1.5× 69 1.4× 67 1.4× 35 792
Sławomir T. Wierzchoń 256 0.7× 51 0.5× 60 0.6× 90 1.8× 71 1.5× 44 596
Telmo M. Silva Filho 443 1.2× 41 0.4× 56 0.6× 43 0.9× 112 2.4× 34 677
Xing He 361 1.0× 48 0.4× 35 0.4× 14 0.3× 66 1.4× 44 770
Mengdi Huai 414 1.1× 59 0.5× 44 0.5× 12 0.2× 62 1.3× 43 580
Xin Tong 205 0.5× 118 1.1× 71 0.8× 69 1.4× 54 1.1× 46 573
Javier G. Castellano 465 1.2× 33 0.3× 106 1.1× 110 2.2× 53 1.1× 25 766
Jorma Laurikkala 378 1.0× 24 0.2× 137 1.5× 20 0.4× 60 1.3× 39 711

Countries citing papers authored by Liuyi Yao

Since Specialization
Citations

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

Fields of papers citing papers by Liuyi Yao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liuyi Yao

This figure shows the co-authorship network connecting the top 25 collaborators of Liuyi Yao. A scholar is included among the top collaborators of Liuyi Yao 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 Liuyi Yao. Liuyi Yao 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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