Lang Wu

471 citations
46 papers · 308 · h-index 10

Impact in

    • Advanced Manufacturing and Logistics Optimization
    • Assembly Line Balancing Optimization
    • Scheduling and Optimization Algorithms
    • Manufacturing Process and Optimization
    • Optimization and Packing Problems
    • 3D Surveying and Cultural Heritage

Papers in

Lang Wu

38 papers receiving 299 citations

Peers

Lang Wu
Comparison fields: 5 of 98
  • Industrial and Manufacturing Engineering 114
  • Geology 18
  • Medical Laboratory Technology 3
  • Computer Vision and Pattern Recognition 37
  • Aerospace Engineering 41
Replace Simon W. Miller with:
Simon W. Miller United States
Zhiyong Chang China
Soyoung Yoo South Korea
Todd Taylor United States
Hongchang Zhang China
Peizhi Shi United Kingdom
Larysa Burtseva Mexico
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Lang Wu relative to Simon W. Miller United States Simon W. Miller's profile →
Citations per field
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Citations per year

Countries citing papers authored by Lang Wu

Since Specialization
Citations

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

Fields of papers citing papers by Lang Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202134
2 202027
3 202127
4 202125
5 201522
6 201819
7 201917
8 202011
9 202010
10 20219
11 20179
12 20239
13 20218
14 20257
15 20227
16 20227
17 20187
18 20197
19 20216
20 20215

About Lang Wu

Lang Wu is a scholar working on Industrial and Manufacturing Engineering, Computer Vision and Pattern Recognition, Aerospace Engineering, Mechanical Engineering and Mechanics of Materials, having authored 46 papers that have together received 308 indexed citations. Recurring topics across this work include Advanced Manufacturing and Logistics Optimization (9 papers), Assembly Line Balancing Optimization (8 papers), Scheduling and Optimization Algorithms (6 papers), Robotics and Sensor-Based Localization (5 papers), Optimization and Packing Problems (4 papers), Advanced Sensor and Energy Harvesting Materials (4 papers), Tactile and Sensory Interactions (3 papers) and Combustion and Detonation Processes (2 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (114 citations), Geology (18 citations), Medical Laboratory Technology (3 citations), Computer Vision and Pattern Recognition (37 citations) and Aerospace Engineering (41 citations). Lang Wu has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Qiang Zhou, Ben Niu, Qing Hao, Yuanyue Feng, Shuting Wang, Yuanlong Xie, Felix T.S. Chan, Jie Meng, Liquan Jiang and Feng Liu. Their work appears in journals such as Computers & Industrial Engineering, Advanced Materials Technologies, Industrial Management & Data Systems, Europhysics Letters (EPL) and Engineering Optimization.

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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