Jiawei Jiang

1.9k citations
98 papers · 1.2k · h-index 21

Impact in

    • Stochastic Gradient Optimization Techniques
    • Privacy-Preserving Technologies in Data
    • Advanced Graph Neural Networks
    • Machine Learning and Data Classification
    • Data Stream Mining Techniques
    • Advanced Neural Network Applications
    • Graph Theory and Algorithms

Papers in

Jiawei Jiang

82 papers receiving 1.2k citations

Peers

Jiawei Jiang
Comparison fields: 5 of 132
  • Artificial Intelligence 671
  • Computer Vision and Pattern Recognition 330
  • Computational Mathematics 6
  • Computer Networks and Communications 231
  • Hardware and Architecture 68
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Min Luo China
Huan Zhao China
Maria Ganzha Poland
Jun Sakuma Japan
Shang Gao China
Shi Han China
Weiwei Fang China
Guangshun Li China
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Citations per field
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Citations per year

Countries citing papers authored by Jiawei Jiang

Since Specialization
Citations

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

Fields of papers citing papers by Jiawei Jiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 98 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017144
2 201871
3 202054
4 201952
5 201751
6 202147
7 202142
8 201939
9 201937
10 201636
11 202428
12 201828
13 202128
14 202126
15 202326
16 202124
17 201923
18 202223
19 202021
20 201921

About Jiawei Jiang

Jiawei Jiang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications, Molecular Biology and Information Systems, having authored 98 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (15 papers), Stochastic Gradient Optimization Techniques (14 papers), Advanced Neural Network Applications (12 papers), Privacy-Preserving Technologies in Data (12 papers), Machine Learning and Data Classification (10 papers), Graph Theory and Algorithms (8 papers), Bone Metabolism and Diseases (6 papers) and Parallel Computing and Optimization Techniques (6 papers). The work is most often cited by research in Artificial Intelligence (671 citations), Computer Vision and Pattern Recognition (330 citations), Computational Mathematics (6 citations), Computer Networks and Communications (231 citations) and Hardware and Architecture (68 citations). Jiawei Jiang has collaborated with scholars based in China, Switzerland and United States. Frequent co-authors include Bin Cui, Lele Yu, Yingxia Shao, Fangcheng Fu, Ce Zhang, Xupeng Miao, Wentao Zhang, Ce Zhang, Tong Yang and Yu Qian. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Proceedings of the VLDB Endowment, The VLDB Journal, IEEE Transactions on Mobile Computing and Food Hydrocolloids.

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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