Liang Ding

5.8k citations
278 papers · 4.2k indexed · h-index 35

Impact in

Papers in

Liang Ding

256 papers receiving 4.1k citations

Peers

Liang Ding
Comparison fields: 5 of 138
  • Control and Systems Engineering 1.9k
  • Civil and Structural Engineering 1.3k
  • Mechanical Engineering 1.4k
  • Biomedical Engineering 1.5k
  • Computer Vision and Pattern Recognition 663
Replace Guangjun Liu with:
Guangjun Liu Canada
Zongquan Deng China
Karl Iagnemma United States
Keiji Nagatani Japan
Inna Sharf Canada
Peter Eberhard Germany
Andreas Kugi Austria
Jun Luo China
Jan Swevers Belgium
Xingjian Jing Hong Kong
Liang Ding relative to Guangjun Liu Canada Guangjun Liu's profile →
Citations per field
00.5×1.5×
Guangjun Liu · 1×
Citations per year

Countries citing papers authored by Liang Ding

Since Specialization
Citations

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

Fields of papers citing papers by Liang Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20251
3 20249
4 20242
5 20243
6 202315
7 20235
8 202237
9 20222
10 202215
11 202216
12 20215
13 202126
14 202123
15 202045
16 201918
17 201813
18 201749
19 201312
20 20127

About Liang Ding

Liang Ding is a scholar working on Civil and Structural Engineering, Control and Systems Engineering, Biomedical Engineering, Mechanical Engineering and Aerospace Engineering, having authored 278 papers that have together received 4.2k indexed citations. Recurring topics across this work include Soil Mechanics and Vehicle Dynamics (93 papers), Robotic Locomotion and Control (86 papers), Control and Dynamics of Mobile Robots (36 papers), Robot Manipulation and Learning (32 papers), Robotic Path Planning Algorithms (31 papers), Planetary Science and Exploration (28 papers), Agricultural Engineering and Mechanization (25 papers) and Prosthetics and Rehabilitation Robotics (24 papers). The work is most often cited by research in Control and Systems Engineering (1.9k citations), Civil and Structural Engineering (1.3k citations), Mechanical Engineering (1.4k citations), Biomedical Engineering (1.5k citations) and Computer Vision and Pattern Recognition (663 citations). Liang Ding has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Haibo Gao, Zongquan Deng, Guangjun Liu, Shu Li, Weihua Li, Kazuya Yoshida, Keiji Nagatani, Zhijun Li, Mahdi Tavakoli and Chao Chen. Their work appears in journals such as IEEE Robotics and Automation Letters, Mechanism and Machine Theory, IEEE Transactions on Systems Man and Cybernetics Systems, Journal of Terramechanics and Mechanical Systems and Signal Processing.

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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