Hao Wei

20 papers receiving 684 citations

Peers

Hao Wei
Comparison fields: 5 of 56
  • Bioengineering 129
  • Signal Processing 141
  • Polymers and Plastics 125
  • Computer Vision and Pattern Recognition 182
  • Computer Networks and Communications 168
Replace Wei Ge with:
Wei Ge China
Yu-Yuan Chen China
Gianluca Piccinini Italy
Kazunori Sugahara Japan
Wenyuan Yang China
Suki Kim South Korea
Seong-je Cho South Korea
M. Yamashina Japan
Jong-Seung Park South Korea
Chenchen Deng China
Hao Wei relative to Wei Ge China Wei Ge's profile →
Citations per field
00.5×4.6×
Wei Ge · 1×
Citations per year

Countries citing papers authored by Hao Wei

Since Specialization
Citations

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

Fields of papers citing papers by Hao Wei

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012296
2 201698
3 201452
4 201646
5 201744
6 201730
7 202326
8 201726
9 201618
10 201712
11 201812
12 20138
13 20257
14 20227
15 20136
16 20204
17
Location Based Services Recommendation with Budget Constraints.
20162
18 20232
19 20171
20 20231

About Hao Wei

Hao Wei is a scholar working on Computer Networks and Communications, Signal Processing, Artificial Intelligence, Computational Theory and Mathematics and Statistical and Nonlinear Physics, having authored 21 papers that have together received 698 indexed citations. Recurring topics across this work include Data Management and Algorithms (6 papers), Complex Network Analysis Techniques (4 papers), Advanced Graph Neural Networks (3 papers), Complexity and Algorithms in Graphs (3 papers), Advanced Database Systems and Queries (3 papers), Caching and Content Delivery (2 papers), Surface Chemistry and Catalysis (2 papers) and Carbon dioxide utilization in catalysis (2 papers). The work is most often cited by research in Bioengineering (129 citations), Signal Processing (141 citations), Polymers and Plastics (125 citations), Computer Vision and Pattern Recognition (182 citations) and Computer Networks and Communications (168 citations). Hao Wei has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Jeffrey Xu Yu, Can Lu, Yanyan Wang, Zhi Yang, Xiaolu Huang, Yu Yuan, Yafei Zhang, Rungang Gao, Nantao Hu and Eric Siu-Wai Kong. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, The VLDB Journal, Proceedings of the VLDB Endowment, IEEE Solid-State Circuits Letters and Journal of the American Chemical Society.

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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