S. Chu

14 total papers · 1.1k total citations
7 papers, 739 citations indexed

About

S. Chu is a scholar working on Signal Processing, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, S. Chu has authored 7 papers receiving a total of 739 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Signal Processing, 4 papers in Artificial Intelligence and 1 paper in Computer Networks and Communications. Recurrent topics in S. Chu's work include Speech and Audio Processing (3 papers), Speech Recognition and Synthesis (3 papers) and Music and Audio Processing (2 papers). S. Chu is often cited by papers focused on Speech and Audio Processing (3 papers), Speech Recognition and Synthesis (3 papers) and Music and Audio Processing (2 papers). S. Chu collaborates with scholars based in United States and China. S. Chu's co-authors include Michael J. Pazzani, David M. Hart, Eamonn Keogh, Chiman Kwan, Jingwei Yin, Yunxin Zhao, K. C. Ho, Junping Yin, Bulent Ayhan and Steve Schaffer and has published in prestigious journals such as Applied Sciences and AGU Fall Meeting Abstracts.

In The Last Decade

S. Chu

6 papers receiving 693 citations

Hit Papers

normalize citations (0→100%) normalize lifespan (0→100%) sort by overperformance

Author Peers

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

Author						Papers	Cites
S. Chu	427	307	114	99	82	7	739
Iqbal Jamal	265 0.6×	361 1.2×	79 0.7×	85 0.9×	74 0.9×	11	665
Liudmila Ulanova	485 1.1×	408 1.3×	105 0.9×	101 1.0×	116 1.4×	11	751
Alain Ketterlin	346 0.8×	229 0.7×	103 0.9×	47 0.5×	90 1.1×	13	761
Hoang Anh Dau	480 1.1×	430 1.4×	98 0.9×	76 0.8×	113 1.4×	12	711
Nurjahan Begum	454 1.1×	396 1.3×	79 0.7×	69 0.7×	119 1.5×	8	628
Congrui Huang	391 0.9×	585 1.9×	61 0.5×	232 2.3×	29 0.4×	8	863
Zhengzheng Xing	393 0.9×	403 1.3×	62 0.5×	48 0.5×	90 1.1×	8	669
Tung Kieu	385 0.9×	414 1.3×	82 0.7×	182 1.8×	22 0.3×	18	792
Usue Mori	332 0.8×	361 1.2×	49 0.4×	158 1.6×	87 1.1×	23	792
Eamonn Keogh	563 1.3×	403 1.3×	130 1.1×	68 0.7×	122 1.5×	15	807

Countries citing papers authored by S. Chu

Since Specialization

Citations

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

Fields of papers citing papers by S. Chu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Chu

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