Dakai Wang

426 citations
30 papers · 285 · h-index 10

Impact in

Papers in

Dakai Wang

24 papers receiving 278 citations

Peers

Dakai Wang
Comparison fields: 5 of 50
  • Polymers and Plastics 81
  • Biomedical Engineering 201
  • Cognitive Neuroscience 84
  • Bioengineering 16
  • Electrical and Electronic Engineering 91
Replace Dongliang Guo with:
Dongliang Guo China
Zekun Li China
Tianyun Dong China
Shuaikang Zheng China
Denglin Zhu China
Wenyang Li China
Amir Servati Canada
Tianming Sun China
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Citations per field
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Dongliang Guo · 1×
Citations per year

Countries citing papers authored by Dakai Wang

Since Specialization
Citations

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

Fields of papers citing papers by Dakai Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202144
2 202243
3 202138
4 202023
5 202222
6 202418
7 202217
8 202214
9 202411
10 20229
11 20239
12 20218
13 19934
14 20204
15 20243
16
Image Filtering by Combination of the Curvature-Driven and Edge-Stopping Nonlinear Diffusion
20083
17 20033
18 20242
19 20242
20 20192

About Dakai Wang

Dakai Wang is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering, Computer Vision and Pattern Recognition, Cognitive Neuroscience and Polymers and Plastics, having authored 30 papers that have together received 285 indexed citations. Recurring topics across this work include Advanced Sensor and Energy Harvesting Materials (10 papers), Advanced DC-DC Converters (8 papers), Tactile and Sensory Interactions (7 papers), Multilevel Inverters and Converters (6 papers), Silicon Carbide Semiconductor Technologies (6 papers), Conducting polymers and applications (5 papers), Advanced Neural Network Applications (4 papers) and Advanced Algorithms and Applications (2 papers). The work is most often cited by research in Polymers and Plastics (81 citations), Biomedical Engineering (201 citations), Cognitive Neuroscience (84 citations), Bioengineering (16 citations) and Electrical and Electronic Engineering (91 citations). Dakai Wang has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Zhiwu Han, Shichao Niu, Linpeng Liu, Junqiu Zhang, Guoliang Ma, Changchao Zhang, Xiancun Meng, Jingxiang Wang, Luquan Ren and Bo Li. Their work appears in journals such as Nano Energy, ACS Applied Materials & Interfaces, Advanced Materials Technologies, Digital Signal Processing and ACS Nano.

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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