Mingzhong Wang

1.4k citations
63 papers · 960 · h-index 15

Impact in

Papers in

Mingzhong Wang

57 papers receiving 931 citations

Peers

Mingzhong Wang
Comparison fields: 5 of 107
  • Artificial Intelligence 564
  • Computer Networks and Communications 302
  • Information Systems 263
  • Signal Processing 99
  • Transportation 45
Replace Xiaoqin Zeng with:
Xiaoqin Zeng China
Giorgio Terracina Italy
Chungang Yan China
Xun Zheng China
Lukáš Chrpa Czechia
Zhenhua Huang China
Neil Shah United States
Shengling Wang China
Tianyi Wang China
Mingzhong Wang relative to Xiaoqin Zeng China Xiaoqin Zeng's profile →
Citations per field
00.5×3.3×
Xiaoqin Zeng · 1×
Citations per year

Countries citing papers authored by Mingzhong Wang

Since Specialization
Citations

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

Fields of papers citing papers by Mingzhong Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013141
2 2017139
3 2019107
4 201470
5 200948
6 201937
7 201630
8 202130
9 201929
10 202129
11 202328
12 200426
13 201924
14 202315
15 201415
16 201814
17 202311
18 201310
19 202310
20 201610

About Mingzhong Wang

Mingzhong Wang is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 63 papers that have together received 960 indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (5 papers), Distributed and Parallel Computing Systems (5 papers), Advanced Graph Neural Networks (5 papers), Scientific Computing and Data Management (5 papers), Human Mobility and Location-Based Analysis (5 papers), Mobile Crowdsensing and Crowdsourcing (4 papers), Music and Audio Processing (4 papers) and Adversarial Robustness in Machine Learning (4 papers). The work is most often cited by research in Artificial Intelligence (564 citations), Computer Networks and Communications (302 citations), Information Systems (263 citations), Signal Processing (99 citations) and Transportation (45 citations). Mingzhong Wang has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Liehuang Zhu, Mingwei Wei, Meng Shen, Xin Li, Yu‐an Tan, Chang Liu, Rui Ye, Kotagiri Ramamohanarao, Jinjun Chen and Xin Li. Their work appears in journals such as Information Sciences, ACM Transactions on Information Systems, IEEE Access, Computing 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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