Yu She

1.5k citations
55 papers · 1.1k · h-index 17

Impact in

Papers in

    • Robot Manipulation and Learning 25
    • Soft Robotics and Applications 16
    • Prosthetics and Rehabilitation Robotics 13
    • Advanced Sensor and Energy Harvesting Materials 8
    • Muscle activation and electromyography studies 7

Yu She

48 papers receiving 1.1k citations

Peers

Yu She
Comparison fields: 5 of 62
  • Control and Systems Engineering 614
  • Biomedical Engineering 723
  • Cognitive Neuroscience 237
  • Human-Computer Interaction 52
  • Mechanical Engineering 284
Replace Houde Liu with:
Houde Liu China
Joshua S. Mehling United States
Hiromi Mochiyama Japan
Hegao Cai China
Shaowei Fan China
Maxime Chalon Germany
Hegao Cai China
Yuji Yamakawa Japan
R. Raymond United States
William Bluethmann United States
Yu She relative to Houde Liu China Houde Liu's profile →
Citations per field
00.5×1.5×2.1×
Houde Liu · 1×
Citations per year

Countries citing papers authored by Yu She

Since Specialization
Citations

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

Fields of papers citing papers by Yu She

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015175
2 2021170
3 202199
4 201679
5 201854
6 201554
7 202054
8 201537
9 201834
10 202431
11 202029
12 201828
13 201627
14 201720
15 201820
16 201717
17 202316
18 201916
19 201514
20 202013

About Yu She

Yu She is a scholar working on Control and Systems Engineering, Biomedical Engineering, Cognitive Neuroscience, Aerospace Engineering and Mechanical Engineering, having authored 55 papers that have together received 1.1k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (25 papers), Soft Robotics and Applications (16 papers), Tactile and Sensory Interactions (13 papers), Prosthetics and Rehabilitation Robotics (13 papers), Advanced Sensor and Energy Harvesting Materials (8 papers), Space Satellite Systems and Control (8 papers), Muscle activation and electromyography studies (7 papers) and Modular Robots and Swarm Intelligence (5 papers). The work is most often cited by research in Control and Systems Engineering (614 citations), Biomedical Engineering (723 citations), Cognitive Neuroscience (237 citations), Human-Computer Interaction (52 citations) and Mechanical Engineering (284 citations). Yu She has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Hai‐Jun Su, Edward H. Adelson, Shaoxiong Wang, Deshan Meng, Chang Li, Siyuan Dong, Hongliang Shi, Wenfu Xu, Alberto Rodríguez and Junmin Wang. Their work appears in journals such as Journal of Mechanisms and Robotics, IEEE Transactions on Automation Science and Engineering, IEEE/ASME Transactions on Mechatronics, Acta Astronautica and IEEE Robotics and Automation Letters.

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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