Daobin Wang

558 citations
53 papers · 351 · h-index 10

Impact in

Papers in

Daobin Wang

47 papers receiving 333 citations

Peers

Daobin Wang
Comparison fields: 5 of 81
  • Transportation 37
  • Building and Construction 47
  • Control and Systems Engineering 58
  • Computer Vision and Pattern Recognition 41
  • Aerospace Engineering 49
Replace Hao Fu with:
Hao Fu China
Can Huang United States
Albert Ting Leung Lee Hong Kong
Han Zhao China
Zhiyong Guo China
Sun Ho Kim South Korea
Zheng Gong China
Jian Du China
Daobin Wang relative to Hao Fu China Hao Fu's profile →
Citations per field
00.5×2.6×
Hao Fu · 1×
Citations per year

Countries citing papers authored by Daobin Wang

Since Specialization
Citations

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

Fields of papers citing papers by Daobin Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201466
2 201945
3 201125
4 201318
5 199618
6 201716
7 200913
8 201210
9 201110
10 201410
11 20259
12 20238
13 20188
14 20088
15 20167
16 20206
17 20176
18 20086
19 20255
20 20205

About Daobin Wang

Daobin Wang is a scholar working on Control and Systems Engineering, Transportation, Building and Construction, Electrical and Electronic Engineering and Atomic and Molecular Physics, and Optics, having authored 53 papers that have together received 351 indexed citations. Recurring topics across this work include Traffic control and management (13 papers), Transportation Planning and Optimization (12 papers), Traffic Prediction and Management Techniques (12 papers), Optical Network Technologies (5 papers), Robotic Path Planning Algorithms (4 papers), Photonic and Optical Devices (4 papers), Robotics and Sensor-Based Localization (4 papers) and Photonic Crystals and Applications (3 papers). The work is most often cited by research in Transportation (37 citations), Building and Construction (47 citations), Control and Systems Engineering (58 citations), Computer Vision and Pattern Recognition (41 citations) and Aerospace Engineering (49 citations). Daobin Wang has collaborated with scholars based in China, United States and Iran. Frequent co-authors include Huawei Liang, Shuai Zhang, Guangchuan Yang, Zong Tian, Hao Xu, Lihua Yuan, Xiaojuan Wu, Jinxi Liu, Cai‐Rong Zhang and Meiling Zhang. Their work appears in journals such as Optical Fiber Technology, Optics Communications, European Journal of Pediatrics, Journal of Advanced Transportation and Scientific Reports.

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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