Liao Wu

2.0k citations
61 papers · 1.5k · h-index 21

Impact in

Papers in

Liao Wu

58 papers receiving 1.4k citations

Peers

Liao Wu
Comparison fields: 5 of 109
  • Control and Systems Engineering 588
  • Biomedical Engineering 827
  • Computer Vision and Pattern Recognition 274
  • Mechanical Engineering 453
  • Industrial and Manufacturing Engineering 71
Replace David Howard with:
David Howard Australia
Xiao Xiao China
Uikyum Kim South Korea
Kenjiro Tadakuma Japan
Chaoyang Shi China
Ketao Zhang United Kingdom
Tianliang Li China
Yingzhong Tian China
Bernard Bayle France
Lina Hao China
Liao Wu relative to David Howard Australia David Howard's profile →
Citations per field
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David Howard · 1×
Citations per year

Countries citing papers authored by Liao Wu

Since Specialization
Citations

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

Fields of papers citing papers by Liao Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016134
2 2013128
3 202394
4 201493
5 201689
6 201677
7 201658
8 201657
9 201754
10 201946
11 202345
12 201640
13 201437
14 201731
15 201730
16 202328
17 202327
18 202126
19 201926
20 201522

About Liao Wu

Liao Wu is a scholar working on Biomedical Engineering, Control and Systems Engineering, Mechanical Engineering, Surgery and Computer Vision and Pattern Recognition, having authored 61 papers that have together received 1.5k indexed citations. Recurring topics across this work include Soft Robotics and Applications (28 papers), Robot Manipulation and Learning (16 papers), Robotic Mechanisms and Dynamics (10 papers), Teleoperation and Haptic Systems (7 papers), Surgical Simulation and Training (6 papers), Advanced Sensor and Energy Harvesting Materials (6 papers), Modular Robots and Swarm Intelligence (5 papers) and Advanced Measurement and Metrology Techniques (5 papers). The work is most often cited by research in Control and Systems Engineering (588 citations), Biomedical Engineering (827 citations), Computer Vision and Pattern Recognition (274 citations), Mechanical Engineering (453 citations) and Industrial and Manufacturing Engineering (71 citations). Liao Wu has collaborated with scholars based in Australia, China and Singapore. Frequent co-authors include Hongliang Ren, Keyu Wu, Ken Chen, Xiangdong Yang, Jonathan Roberts, Ross Crawford, Haoyong Yu, Zheng Li, Jinquan Li and Jiaole Wang. Their work appears in journals such as IEEE Access, IEEE/ASME Transactions on Mechatronics, IEEE Robotics and Automation Letters, ACS Applied Materials & Interfaces and Advanced Functional Materials.

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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