Jun Shu

611 citations
31 papers · 438 · h-index 11

Impact in

Papers in

Jun Shu

25 papers receiving 433 citations

Peers

Jun Shu
Comparison fields: 5 of 62
  • Cognitive Neuroscience 292
  • Experimental and Cognitive Psychology 134
  • Human-Computer Interaction 42
  • Management of Technology and Innovation 24
  • Signal Processing 35
Replace Saeid Moslehpour with:
Saeid Moslehpour United States
Baoyun Lu China
Francesco Leotta Italy
Adhi Dharma Wibawa Indonesia
Martyn Ratcliffe United Kingdom
Małgorzata Plechawska–Wójcik Poland
Xue Jiang China
Debashis Das Chakladar India
Shiwei Cheng China
Samit Bhattacharya India
Jun Shu relative to Saeid Moslehpour United States Saeid Moslehpour's profile →
Citations per field
00.5×4.6×
Saeid Moslehpour · 1×
Citations per year

Countries citing papers authored by Jun Shu

Since Specialization
Citations

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

Fields of papers citing papers by Jun Shu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020130
2 202159
3 201843
4 202134
5 202229
6 200929
7 202218
8 201216
9
Challenges in RFID enabled supply chain management
200616
10 202013
11 201912
12 20217
13 20216
14 20225
15 20214
16 20184
17
A Customer's Outage Cost Assessment Approach Based on the Improved Tobit Model
20103
18
Coordinative Optimization of Network Loss in Security-Constrained Economic Dispatching
20103
19 20251
20
Octree-based blind watermarking on 3D meshes
20081

About Jun Shu

Jun Shu is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Control and Systems Engineering, having authored 31 papers that have together received 438 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (16 papers), Neural dynamics and brain function (14 papers), Emotion and Mood Recognition (5 papers), Neural and Behavioral Psychology Studies (3 papers), Blind Source Separation Techniques (3 papers), Functional Brain Connectivity Studies (3 papers), Advanced Algorithms and Applications (2 papers) and Power Systems and Renewable Energy (2 papers). The work is most often cited by research in Cognitive Neuroscience (292 citations), Experimental and Cognitive Psychology (134 citations), Human-Computer Interaction (42 citations), Management of Technology and Innovation (24 citations) and Signal Processing (35 citations). Jun Shu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Ying Zeng, Li Tong, Bin Yan, Ning Zhuang, Kai Yang, Linyuan Wang, Kai Yang, Russell R. Barton, Bin Yan and Seung Ki Moon. Their work appears in journals such as Frontiers in Human Neuroscience, Production and Operations Management, Dianli xitong zidonghua, Frontiers in Neurorobotics and Neuroscience.

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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