Lu Dong

64 papers receiving 1.4k citations

Peers

Lu Dong
Comparison fields: 5 of 80
  • Control and Systems Engineering 782
  • Computational Theory and Mathematics 520
  • Artificial Intelligence 432
  • Computer Networks and Communications 266
  • Computer Vision and Pattern Recognition 232
Replace Hao Xu with:
Hao Xu United States
Dapeng Li China
Zhiqiang Pu China
Jin‐Xi Zhang China
Dengxiu Yu China
Aydın Yeşildirek United States
Abdesselem Boulkroune Algeria
Howard M. Schwartz Canada
Luis T. Aguilar Mexico
Tyler Summers United States
Lu Dong relative to Hao Xu United States Hao Xu's profile →
Citations per field
00.5×1.5×2.5×
Hao Xu · 1×
Citations per year

Countries citing papers authored by Lu Dong

Since Specialization
Citations

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

Fields of papers citing papers by Lu Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 75 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016182
2 2016154
3 2016150
4 2020101
5 202180
6 201974
7 201870
8 202062
9 202362
10 202161
11 202045
12 202036
13 201434
14 202231
15 202130
16 202325
17 202022
18 202218
19 202018
20 202217

About Lu Dong

Lu Dong is a scholar working on Artificial Intelligence, Control and Systems Engineering, Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 75 papers that have together received 1.5k indexed citations. Recurring topics across this work include Adaptive Dynamic Programming Control (24 papers), Reinforcement Learning in Robotics (22 papers), Adaptive Control of Nonlinear Systems (18 papers), Distributed Control Multi-Agent Systems (11 papers), Robotic Path Planning Algorithms (8 papers), UAV Applications and Optimization (5 papers), Frequency Control in Power Systems (5 papers) and Control and Dynamics of Mobile Robots (5 papers). The work is most often cited by research in Control and Systems Engineering (782 citations), Computational Theory and Mathematics (520 citations), Artificial Intelligence (432 citations), Computer Networks and Communications (266 citations) and Computer Vision and Pattern Recognition (232 citations). Lu Dong has collaborated with scholars based in China, United States and Bangladesh. Frequent co-authors include Changyin Sun, Haibo He, X. Zhong, Yuncheng Ouyang, Zichen He, Lei Xue, Yufei Tang, Yuanda Wang, Haibo He and Chunwei Song. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, IEEE/CAA Journal of Automatica Sinica, IEEE Transactions on Fuzzy Systems, Neural Computing and Applications and IEEE Transactions on Cybernetics.

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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