Liangyue Li

62 total papers · 615 total citations
35 papers, 388 citations indexed

About

Liangyue Li is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Liangyue Li has authored 35 papers receiving a total of 388 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 13 papers in Information Systems and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Liangyue Li's work include Advanced Graph Neural Networks (10 papers), Recommender Systems and Techniques (9 papers) and Topic Modeling (7 papers). Liangyue Li is often cited by papers focused on Advanced Graph Neural Networks (10 papers), Recommender Systems and Techniques (9 papers) and Topic Modeling (7 papers). Liangyue Li collaborates with scholars based in United States, China and Germany. Liangyue Li's co-authors include Hanghang Tong, Yun Fu, Sheng Li, Nan Cao, Yu‐Ru Lin, Norbou Buchler, Yun Fu, Sheng Li, Kate Ehrlich and Jaewon Yang and has published in prestigious journals such as IEEE Transactions on Knowledge and Data Engineering, Image and Vision Computing and ACM Transactions on Information Systems.

In The Last Decade

Liangyue Li

33 papers receiving 384 citations

Author Peers

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

Author						Papers	Cites
Liangyue Li	193	155	86	80	54	35	388
Rong Jin	164 0.8×	125 0.8×	81 0.9×	18 0.2×	60 1.1×	44	406
Yiqun Zhang	275 1.4×	143 0.9×	89 1.0×	31 0.4×	12 0.2×	54	414
Yuntao Jia	117 0.6×	153 1.0×	71 0.8×	144 1.8×	27 0.5×	14	352
Xingzhong Du	181 0.9×	171 1.1×	197 2.3×	29 0.4×	23 0.4×	26	403
Meiyu Liang	213 1.1×	196 1.3×	58 0.7×	32 0.4×	8 0.1×	61	381
Christopher Musco	218 1.1×	84 0.5×	41 0.5×	59 0.7×	81 1.5×	26	411
Jishang Wei	215 1.1×	198 1.3×	26 0.3×	29 0.4×	17 0.3×	26	435
Hayato Kobayashi	256 1.3×	105 0.7×	47 0.5×	18 0.2×	56 1.0×	31	443
Junli Li	129 0.7×	88 0.6×	78 0.9×	58 0.7×	7 0.1×	31	384
Weijie Fu	288 1.5×	229 1.5×	61 0.7×	26 0.3×	14 0.3×	17	446

Countries citing papers authored by Liangyue Li

Since Specialization

Citations

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

Fields of papers citing papers by Liangyue Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liangyue Li

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