Minglong Lei
Impact in
- Artificial Intelligence top 5%
- Advanced Graph Neural Networks
- Topic Modeling
- Imbalanced Data Classification Techniques
- Text and Document Classification Technologies
- Accounting top 10%
- Financial Distress and Bankruptcy Prediction
Papers in
-
- Advanced Graph Neural Networks 13
- Domain Adaptation and Few-Shot Learning 4
- Topic Modeling 4
- Natural Language Processing Techniques 2
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- Complex Network Analysis Techniques 9
- Co-authors
- Yong Shi (10 shared papers)Junzhong Ji (10 shared papers)Pei Quan (8 shared papers)Lingfeng Niu (15 shared papers)Yi Qu (1 shared paper)Yang Xiao (5 shared papers)Jia Li (1 shared paper)Hong Yang (2 shared papers)
- Journals
- Neural Networks (4 papers)Information Sciences (2 papers)IEEE Transactions on Cybernetics (2 papers)Engineering Applications of Artificial Intelligence (1 paper)The Visual Computer (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Minglong Lei
25 papers receiving 350 citations
Peers
Comparison fields: 5 of 78
- Artificial Intelligence 210
- Accounting 49
- Statistical and Nonlinear Physics 39
- Computer Vision and Pattern Recognition 64
- Cognitive Neuroscience 40
Countries citing papers authored by Minglong Lei
This map shows the geographic impact of Minglong Lei'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 Minglong Lei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Minglong Lei more than expected).
Fields of papers citing papers by Minglong Lei
This network shows the impact of papers produced by Minglong Lei. 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 Minglong Lei. The network helps show where Minglong Lei may publish in the future.
Co-authors
The 25 scholars most cited alongside Minglong Lei, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 65 | |
| 2 | 2022 | 45 | |
| 3 | 2020 | 29 | |
| 4 | 2022 | 20 | |
| 5 | 2022 | 20 | |
| 6 | 2018 | 20 | |
| 7 | 2022 | 17 | |
| 8 | 2022 | 16 | |
| 9 | 2021 | 15 | |
| 10 | 2023 | 14 | |
| 11 | 2020 | 14 | |
| 12 | 2024 | 12 | |
| 13 | 2022 | 12 | |
| 14 | 2019 | 9 | |
| 15 | 2022 | 9 | |
| 16 | 2019 | 8 | |
| 17 | 2022 | 7 | |
| 18 | 2021 | 7 | |
| 19 | 2020 | 5 | |
| 20 | 2019 | 5 |
About Minglong Lei
Minglong Lei is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Signal Processing and Transportation, having authored 29 papers that have together received 362 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (13 papers), Complex Network Analysis Techniques (9 papers), Domain Adaptation and Few-Shot Learning (4 papers), Topic Modeling (4 papers), Traffic Prediction and Management Techniques (3 papers), Graph Theory and Algorithms (3 papers), Time Series Analysis and Forecasting (3 papers) and Natural Language Processing Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (210 citations), Accounting (49 citations), Statistical and Nonlinear Physics (39 citations), Computer Vision and Pattern Recognition (64 citations) and Cognitive Neuroscience (40 citations). Minglong Lei has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Yong Shi, Junzhong Ji, Pei Quan, Lingfeng Niu, Yi Qu, Yang Xiao, Jia Li, Hong Yang, Rongrong Ma and Yongduan Song. Their work appears in journals such as Neural Networks, Information Sciences, IEEE Transactions on Cybernetics, Engineering Applications of Artificial Intelligence and The Visual Computer.
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.