Mingyi Zhang
- Artificial Intelligence top 10%
- Logic, Reasoning, and Knowledge 21
- Multi-Agent Systems and Negotiation 11
- Logic, programming, and type systems 11
- AI-based Problem Solving and Planning 7
- Domain Adaptation and Few-Shot Learning 4
- Bayesian Modeling and Causal Inference 4
- Semantic Web and Ontologies 4
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- Multimodal Machine Learning Applications 4
- Co-authors
- Yisong WangQuan LuoXuefeng LüMartin HagemannYangkai DuanShou‐Tian ZhengGuo‐Yu YangGuang‐Zhen Liu
- Cited by
- Artificial IntelligenceRenewable Energy, Sustainability and the EnvironmentInorganic Chemistry
In The Last Decade
Mingyi Zhang
47 papers receiving 515 citations
Peers
Comparison fields: 5 of 109
- Artificial Intelligence 137
- Renewable Energy, Sustainability and the Environment 65
- Inorganic Chemistry 41
- Electronic, Optical and Magnetic Materials 47
- Computational Theory and Mathematics 32
Countries citing papers authored by Mingyi Zhang
This map shows the geographic impact of Mingyi 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 Mingyi Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingyi Zhang more than expected).
Fields of papers citing papers by Mingyi Zhang
This network shows the impact of papers produced by Mingyi 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 Mingyi Zhang. The network helps show where Mingyi Zhang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mingyi 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 | 2024 | 4 | |
| 2 | 2024 | 5 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 14 | |
| 5 | 2023 | 7 | |
| 6 | 2023 | 5 | |
| 7 | 2022 | 4 | |
| 8 | 2021 | 8 | |
| 9 | 2020 | 19 | |
| 10 | 2019 | 46 | |
| 11 | Forgetting for answer set programs revisited | 2013 | 16 |
| 12 | 2013 | 3 | |
| 13 | Forgetting in logic programs under strong equivalence | 2012 | 11 |
| 14 | 2011 | 2 | |
| 15 | 2011 | 6 | |
| 16 | Axiom P and Reliable Belief Change Operator in belief revision. | 2008 | 1 |
| 17 | 2007 | 2 | |
| 18 | On the equivalence between answer sets and models of completion for nested logic programs | 2003 | 6 |
| 19 | 1999 | 0 | |
| 20 | Approximation of indistinct concepts | 1989 | 0 |
About Mingyi Zhang
Mingyi Zhang is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition, having authored 52 papers that have together received 524 indexed citations. Recurring topics across this work include Logic, Reasoning, and Knowledge (21 papers), Multi-Agent Systems and Negotiation (11 papers), Logic, programming, and type systems (11 papers), AI-based Problem Solving and Planning (7 papers), Multimodal Machine Learning Applications (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Bayesian Modeling and Causal Inference (4 papers) and Semantic Web and Ontologies (4 papers). The work is most often cited by research in Artificial Intelligence (137 citations), Renewable Energy, Sustainability and the Environment (65 citations) and Inorganic Chemistry (41 citations). Mingyi Zhang has collaborated with scholars based in China, Canada and Hong Kong. Frequent co-authors include Yisong Wang, Quan Luo, Xuefeng Lü, Martin Hagemann, Yangkai Duan, Shou‐Tian Zheng, Guo‐Yu Yang, Guang‐Zhen Liu, Zhiqiang Cao and Jian Zhou. Their work appears in journals such as Applied and Environmental Microbiology, IEEE Transactions on Industrial Electronics and Nanoscale.
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.