Zeyu Jin

1.0k citations
41 papers · 493 · h-index 12

Impact in

Papers in

Zeyu Jin

38 papers receiving 464 citations

Peers

Zeyu Jin
Comparison fields: 5 of 50
  • Signal Processing 378
  • Artificial Intelligence 253
  • Computer Vision and Pattern Recognition 133
  • Cognitive Neuroscience 74
  • Human-Computer Interaction 15
Replace Nicola Montecchio with:
Nicola Montecchio Italy
Frederic Font Spain
Evandro Gouvêa United States
Etienne Marcheret United States
Satoru Fukayama Japan
Takuya Nishimoto Japan
Tomoyasu Nakano Japan
Israel D. Gebru United States
Jaesung Huh South Korea
Daichi Mochihashi Japan
Zeyu Jin relative to Nicola Montecchio Italy Nicola Montecchio's profile →
Citations per field
00.5×11.4×
Nicola Montecchio · 1×
Citations per year

Countries citing papers authored by Zeyu Jin

Since Specialization
Citations

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

Fields of papers citing papers by Zeyu Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Zeyu Jin, 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 Zeyu Jin Line = papers co-authored together Zeyu Jin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202081
2 201854
3 202051
4 202135
5 202033
6 202129
7 201729
8 201620
9 202020
10 202019
11 202017
12 201913
13 201910
14 20149
15 20227
16 20247
17 20246
18 20226
19 20255
20 20225

About Zeyu Jin

Zeyu Jin is a scholar working on Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Renewable Energy, Sustainability and the Environment, having authored 41 papers that have together received 493 indexed citations. Recurring topics across this work include Music and Audio Processing (25 papers), Speech and Audio Processing (23 papers), Speech Recognition and Synthesis (17 papers), Music Technology and Sound Studies (5 papers), Fuel Cells and Related Materials (5 papers), Electrocatalysts for Energy Conversion (5 papers), Hearing Loss and Rehabilitation (3 papers) and Sentiment Analysis and Opinion Mining (2 papers). The work is most often cited by research in Signal Processing (378 citations), Artificial Intelligence (253 citations), Computer Vision and Pattern Recognition (133 citations), Cognitive Neuroscience (74 citations) and Human-Computer Interaction (15 citations). Zeyu Jin has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include Adam Finkelstein, Jiaqi Su, Gautham J. Mysore, Jingwan Lu, Mark Hasegawa‐Johnson, Kaizhi Qian, Nicholas J. Bryan, Stephen DiVerdi, Emma Frid and Richard Zhang. Their work appears in journals such as Chinese Chemical Letters, Materials Science and Engineering R Reports, Journal of Neuroscience, Multiscale Modeling and Simulation and ACM Transactions on Graphics.

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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