Min Chu

93 total papers · 1.1k total citations
59 papers, 704 citations indexed

About

Min Chu is a scholar working on Artificial Intelligence, Signal Processing and Electrical and Electronic Engineering. According to data from OpenAlex, Min Chu has authored 59 papers receiving a total of 704 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 21 papers in Signal Processing and 12 papers in Electrical and Electronic Engineering. Recurrent topics in Min Chu's work include Speech Recognition and Synthesis (32 papers), Speech and Audio Processing (16 papers) and Natural Language Processing Techniques (13 papers). Min Chu is often cited by papers focused on Speech Recognition and Synthesis (32 papers), Speech and Audio Processing (16 papers) and Natural Language Processing Techniques (13 papers). Min Chu collaborates with scholars based in China, United States and United Kingdom. Min Chu's co-authors include Eric Chang, D.J. Allstot, Yao Qian, Frank K. Soong, Yong Zhao, Yining Chen, Chao Huang, Yong Zhao, Peng Hu and Jian-Lai Zhou and has published in prestigious journals such as Sensors, IEEE Sensors Journal and IEEE Transactions on Audio Speech and Language Processing.

In The Last Decade

Min Chu

57 papers receiving 611 citations

Author Peers

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

Author						Papers	Cites
Min Chu	557	317	149	85	40	59	704
Shingo Kuroiwa	429 0.8×	288 0.9×	60 0.4×	112 1.3×	102 2.5×	140	762
Minghui Dong	491 0.9×	328 1.0×	160 1.1×	84 1.0×	208 5.2×	79	905
George Kokkinakis	569 1.0×	284 0.9×	40 0.3×	29 0.3×	91 2.3×	54	800
Zdravko Kačič	546 1.0×	410 1.3×	138 0.9×	17 0.2×	116 2.9×	90	774
Suryakanth V. Gangashetty	484 0.9×	475 1.5×	156 1.0×	18 0.2×	82 2.0×	93	711
Hsiao-Chuan Wang	474 0.9×	497 1.6×	62 0.4×	97 1.1×	117 2.9×	97	778
Ascensión Gallardo-Antolín	394 0.7×	290 0.9×	100 0.7×	23 0.3×	121 3.0×	58	714
Takenori Yoshimura	549 1.0×	409 1.3×	20 0.1×	105 1.2×	96 2.4×	38	841
M.A. Jack	317 0.6×	285 0.9×	29 0.2×	99 1.2×	114 2.9×	69	669
Néstor Becerra Yoma	396 0.7×	312 1.0×	80 0.5×	24 0.3×	68 1.7×	77	632

Countries citing papers authored by Min Chu

Since Specialization

Citations

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

Fields of papers citing papers by Min Chu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Min Chu

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