Gaocai Wang
- Electrical and Electronic Engineering
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition
- Building and Construction
- Artificial Intelligence
- Co-authors
- Yuting LüShuqiang HuangXianfei HuangJianer ChenGuojun WangXin ZhengTaoshen LiZhiguang Shan
- Topics
- Interconnection Networks and Systems (11 papers)IoT and Edge/Fog Computing (8 papers)Advanced Wireless Network Optimization (7 papers)
- Partner nations
- ChinaUnited States
In The Last Decade
Gaocai Wang
54 papers receiving 240 citations
Peers
Comparison fields: 5 of 61
- Electrical and Electronic Engineering 115
- Computer Networks and Communications 103
- Computer Vision and Pattern Recognition 33
- Building and Construction 31
- Artificial Intelligence 28
Countries citing papers authored by Gaocai Wang
This map shows the geographic impact of Gaocai 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 Gaocai Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gaocai Wang more than expected).
Fields of papers citing papers by Gaocai Wang
This network shows the impact of papers produced by Gaocai 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 Gaocai Wang. The network helps show where Gaocai Wang may publish in the future.
Co-authorship network of co-authors of Gaocai Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Gaocai Wang. A scholar is included among the top collaborators of Gaocai Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gaocai Wang. Gaocai Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 0 | |
| 11 | 1 | |
| 12 | 5 | |
| 13 | Secure Data Aggregation for Top- k Queries in Tiered Wireless Sensor Networks. | 7 |
| 14 | 10 | |
| 15 | Efficient Network Multi-outlet Traffic Schedule Scheme | 0 |
| 16 | Design of H-infinity multi-step predictor for descriptor systems | 1 |
| 17 | 5 | |
| 18 | 1 | |
| 19 | 4 | |
| 20 | 2 |
About Gaocai Wang
Gaocai Wang is a scholar working on Computer Networks and Communications, Hardware and Architecture and Computer Vision and Pattern Recognition, having authored 59 papers that have together received 250 indexed citations. Recurring topics across this work include Interconnection Networks and Systems (11 papers), IoT and Edge/Fog Computing (8 papers) and Advanced Wireless Network Optimization (7 papers). The work is most often cited by research in Computer Networks and Communications (103 citations), Hardware and Architecture (17 citations) and Building and Construction (31 citations). Gaocai Wang has collaborated with scholars based in China and United States. Frequent co-authors include Yuting Lü, Shuqiang Huang, Xianfei Huang, Jianer Chen, Guojun Wang, Xin Zheng, Taoshen Li, Zhiguang Shan, Ziyu Peng and Ying Peng. Their work appears in journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.
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.