Ming Zhang
- Artificial Intelligence top 0.5%
- Advanced Graph Neural Networks 31
- Topic Modeling 23
- Text and Document Classification Technologies 14
- Natural Language Processing Techniques 10
- Domain Adaptation and Few-Shot Learning 9
- Information Systems top 0.5%
- Recommender Systems and Techniques 23
- Information Systems Education and Curriculum Development 8
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- Complex Network Analysis Techniques 10
- Signal Processing top 2%
- Transportation top 5%
- Journals
- Nature Communications (1 paper)SHILAP Revista de lepidopterología (1 paper)Renewable and Sustainable Energy Reviews (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Ming Zhang
118 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 158
- Artificial Intelligence 1.7k
- Information Systems 1.1k
- Statistical and Nonlinear Physics 408
- Signal Processing 268
- Transportation 141
Countries citing papers authored by Ming Zhang
This map shows the geographic impact of Ming Zhang'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 Ming Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Zhang more than expected).
Fields of papers citing papers by Ming Zhang
This network shows the impact of papers produced by Ming Zhang. 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 Ming Zhang. The network helps show where Ming Zhang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ming Zhang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 2 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 30 | |
| 5 | 2024 | 16 | |
| 6 | 2024 | 34 | |
| 7 | 2024 | 1 | |
| 8 | 2023 | 30 | |
| 9 | 2023 | 10 | |
| 10 | 2023 | 35 | |
| 11 | 2023 | 45 | |
| 12 | 2023 | 44 | |
| 13 | 2023 | 22 | |
| 14 | 2023 | 46 | |
| 15 | 2023 | 8 | |
| 16 | 2022 | 52 | |
| 17 | 2022 | 37 | |
| 18 | 2022 | 44 | |
| 19 | 2021 | 22 | |
| 20 | Personalized Recommendation Algorithm on Microblogs | 2012 | 3 |
About Ming Zhang
Ming Zhang is a scholar working on Artificial Intelligence, Information Systems and Computer Science Applications, having authored 126 papers that have together received 3.2k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (31 papers), Topic Modeling (23 papers), Recommender Systems and Techniques (23 papers), Text and Document Classification Technologies (14 papers), Natural Language Processing Techniques (10 papers), Complex Network Analysis Techniques (10 papers), Domain Adaptation and Few-Shot Learning (9 papers) and Information Systems Education and Curriculum Development (8 papers). The work is most often cited by research in Artificial Intelligence (1.7k citations), Information Systems (1.1k citations) and Statistical and Nonlinear Physics (408 citations). Ming Zhang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Wei Ju, Xiao Luo, Qiaozhu Mei, Dong Zhang, Haoyuan Li, Yi Wang, Edward Yi Chang, Feng Qian, Xiaolong Wang and Ming Zhou. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and Renewable and Sustainable Energy Reviews.
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.