Lan Wu

486 citations
25 papers · 393 · h-index 8

Impact in

Papers in

Lan Wu

22 papers receiving 388 citations

Peers

Lan Wu
Comparison fields: 5 of 48
  • Polymers and Plastics 137
  • Electrical and Electronic Engineering 277
  • Materials Chemistry 187
  • Computer Vision and Pattern Recognition 41
  • Control and Systems Engineering 40
Replace Yusen Wang with:
Yusen Wang China
Zhentao Li China
Mohit Bajaj India
Niclas Persson Sweden
Dan Huang China
Pengfei Du China
Xiangdong Meng China
Yipeng Wang Hong Kong
Amjad Ullah Pakistan
Jong-Chan Lee South Korea
Lan Wu relative to Yusen Wang China Yusen Wang's profile →
Citations per field
00.5×20×40×51×
Yusen Wang · 1×
Citations per year

Countries citing papers authored by Lan Wu

Since Specialization
Citations

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

Fields of papers citing papers by Lan Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017266
2 201419
3 202116
4 202113
5 202312
6 202010
7 201810
8 20237
9 20127
10 20145
11 20144
12 20174
13 20094
14 20083
15 20242
16 20242
17 20112
18 20232
19 20072
20 20251

About Lan Wu

Lan Wu is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering, Artificial Intelligence, Aerospace Engineering and Electrical and Electronic Engineering, having authored 25 papers that have together received 393 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (6 papers), Robot Manipulation and Learning (4 papers), Gaussian Processes and Bayesian Inference (4 papers), Robotic Path Planning Algorithms (3 papers), Advanced Vision and Imaging (3 papers), Spectroscopy and Chemometric Analyses (2 papers), 3D Surveying and Cultural Heritage (2 papers) and Perovskite Materials and Applications (2 papers). The work is most often cited by research in Polymers and Plastics (137 citations), Electrical and Electronic Engineering (277 citations), Materials Chemistry (187 citations), Computer Vision and Pattern Recognition (41 citations) and Control and Systems Engineering (40 citations). Lan Wu has collaborated with scholars based in Australia, China and Germany. Frequent co-authors include Qingbo Meng, Peng Zhou, Yong Peng, Zhiliang Ku, Xinxin Yu, Jiangjian Shi, Xueping Liu, Yi‐Bing Cheng, Xiaokun Yang and Tianshi Qin. Their work appears in journals such as IEEE Robotics and Automation Letters, Advanced Energy Materials, Transportation Research Part C Emerging Technologies, The Journal of Engineering and IEEE Transactions on Robotics.

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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