Yaohui Jin

2.4k citations
167 papers · 1.5k indexed · h-index 19

Impact in

Papers in

Yaohui Jin

145 papers receiving 1.5k citations

Peers

Yaohui Jin
Comparison fields: 5 of 101
  • Computer Networks and Communications 563
  • Transportation 112
  • Artificial Intelligence 523
  • Signal Processing 140
  • Information Systems 234
Replace Xiaoxian Yang with:
Xiaoxian Yang China
Tian Zhao United States
Xiaolong Xu China
Hao Yue United States
Junde Song China
Huandong Wang China
Wen-Chih Peng Taiwan
Chang Xu China
Xu Zheng China
Yaohui Jin relative to Xiaoxian Yang China Xiaoxian Yang's profile →
Citations per field
00.5×10×13.3×
Xiaoxian Yang · 1×
Citations per year

Countries citing papers authored by Yaohui Jin

Since Specialization
Citations

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

Fields of papers citing papers by Yaohui Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20252
2 20250
3 20250
4 20251
5 20250
6 20250
7 20247
8 202410
9 20244
10 202411
11 20231
12 202311
13 20232
14 202316
15 202311
16 202111
17 202015
18 202010
19
Learning What to Share: Leaky Multi-Task Network for Text Classification
20188
20
Virtualized optical network services across multiple domains for grid applications
20101

About Yaohui Jin

Yaohui Jin is a scholar working on Computer Networks and Communications, Transportation, Electrical and Electronic Engineering, Artificial Intelligence and Information Systems, having authored 167 papers that have together received 1.5k indexed citations. Recurring topics across this work include Advanced Optical Network Technologies (55 papers), Optical Network Technologies (40 papers), Software-Defined Networks and 5G (29 papers), Advanced Photonic Communication Systems (29 papers), Interconnection Networks and Systems (20 papers), Cloud Computing and Resource Management (19 papers), Network Traffic and Congestion Control (18 papers) and Topic Modeling (17 papers). The work is most often cited by research in Computer Networks and Communications (563 citations), Transportation (112 citations), Artificial Intelligence (523 citations), Signal Processing (140 citations) and Information Systems (234 citations). Yaohui Jin has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Weisheng Hu, Long-yuan Li, Junchi Yan, Weiqiang Sun, Liqiang Xiao, Honglun Zhang, Yongkun Wang, Haiyang Wang, Wenqing Chen and Hao He. Their work appears in journals such as Journal of Lightwave Technology, Photonic Network Communications, IEEE Communications Magazine, IEEE Photonics Technology Letters and Journal of Optical Networking.

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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