Guangsen Wang

856 citations
51 papers · 511 · h-index 12

Impact in

    • Speech and Audio Processing
    • Music and Audio Processing
    • Speech Recognition and Synthesis
    • Natural Language Processing Techniques
    • Topic Modeling
    • Speech and dialogue systems

Papers in

Guangsen Wang

47 papers receiving 463 citations

Peers

Guangsen Wang
Comparison fields: 5 of 51
  • Signal Processing 277
  • Artificial Intelligence 392
  • Computer Vision and Pattern Recognition 57
  • Health Informatics 2
  • Control and Systems Engineering 32
Replace Junjie Yang with:
Junjie Yang China
David Macêdo Brazil
Pradhumna Lal Shrestha United States
Edgard Jamhour Brazil
P. Campolucci Italy
Sara Al-Emadi Qatar
Fuhao Li United States
Andrew Kwong United States
Thilo Strauss United States
Chee Chong United States
Guangsen Wang relative to Junjie Yang China Junjie Yang's profile →
Citations per field
00.5×3.8×
Junjie Yang · 1×
Citations per year

Countries citing papers authored by Guangsen Wang

Since Specialization
Citations

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

Fields of papers citing papers by Guangsen Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Guangsen Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Guangsen Wang Line = papers co-authored together Guangsen Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015100
2 201955
3 201946
4 201838
5 202038
6 202329
7 202018
8 201617
9 202316
10 201115
11 201013
12 200911
13 201411
14 20219
15 20169
16 20189
17 20086
18 20226
19 20125
20 20194

About Guangsen Wang

Guangsen Wang is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Signal Processing, Control and Systems Engineering and Automotive Engineering, having authored 51 papers that have together received 511 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (20 papers), Speech and Audio Processing (13 papers), Natural Language Processing Techniques (9 papers), Music and Audio Processing (9 papers), Multilevel Inverters and Converters (6 papers), Real-time simulation and control systems (6 papers), HVDC Systems and Fault Protection (5 papers) and Advanced DC-DC Converters (5 papers). The work is most often cited by research in Signal Processing (277 citations), Artificial Intelligence (392 citations), Computer Vision and Pattern Recognition (57 citations), Health Informatics (2 citations) and Control and Systems Engineering (32 citations). Guangsen Wang has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Dan Su, Dong Yu, Chao Weng, Khe Chai Sim, Lei Xie, Min Luo, Changhao Shan, Bin Ma, Kong Aik Lee and Anthony Larcher. Their work appears in journals such as Electric Power Systems Research, International Journal of Circuit Theory and Applications, IEEE Transactions on Plasma Science, Applied Sciences and Electronics.

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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