Jian Luan

78 total papers · 405 total citations
22 papers, 163 citations indexed

About

Jian Luan is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jian Luan has authored 22 papers receiving a total of 163 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 11 papers in Signal Processing and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jian Luan's work include Speech Recognition and Synthesis (13 papers), Music and Audio Processing (11 papers) and Speech and Audio Processing (9 papers). Jian Luan is often cited by papers focused on Speech Recognition and Synthesis (13 papers), Music and Audio Processing (11 papers) and Speech and Audio Processing (9 papers). Jian Luan collaborates with scholars based in China, United States and Spain. Jian Luan's co-authors include Xu Tan, Xu Tan, Zhou Zhao, Tie‐Yan Liu, Yi Ren, Tao Qin, Jie Wu, Frank K. Soong, Wei Liu and Jie Wu and has published in prestigious journals such as ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

In The Last Decade

Jian Luan

15 papers receiving 155 citations

Author Peers

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

Author Last Decade Papers Cites
Jian Luan 117 115 33 10 8 22 163
Ziqiang Zhang 87 0.7× 149 1.3× 19 0.6× 4 0.4× 5 0.6× 26 202
Sree Hari Krishnan Parthasarathi 148 1.3× 159 1.4× 16 0.5× 11 1.1× 7 0.9× 17 189
Soham Deshmukh 140 1.2× 121 1.1× 65 2.0× 7 0.7× 11 1.4× 14 228
Xu Xiang 170 1.5× 203 1.8× 29 0.9× 10 1.0× 5 0.6× 22 243
Laurent Besacier 61 0.5× 76 0.7× 48 1.5× 6 0.6× 6 0.8× 15 139
Weiwei Lin 158 1.4× 180 1.6× 16 0.5× 5 0.5× 4 0.5× 26 206
Takafumi Koshinaka 190 1.6× 194 1.7× 24 0.7× 15 1.5× 4 0.5× 27 236
Shuai Wang 206 1.8× 212 1.8× 47 1.4× 10 1.0× 6 0.8× 22 292
Marijn Huijbregts 210 1.8× 230 2.0× 42 1.3× 7 0.7× 5 0.6× 23 278
M. Mahajan 83 0.7× 220 1.9× 29 0.9× 14 1.4× 9 1.1× 12 246

Countries citing papers authored by Jian Luan

Since Specialization
Citations

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

Fields of papers citing papers by Jian Luan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jian Luan

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