Minglong Lei
Impact in
- Artificial Intelligence top 10%
- Advanced Graph Neural Networks
- Topic Modeling
- Imbalanced Data Classification Techniques
- Natural Language Processing Techniques
- Accounting top 10%
- Financial Distress and Bankruptcy Prediction
Papers in
-
- Advanced Graph Neural Networks 14
- Domain Adaptation and Few-Shot Learning 4
- Topic Modeling 4
-
- Complex Network Analysis Techniques 10
- Co-authors
- Yong Shi (11 shared papers)Junzhong Ji (10 shared papers)Pei Quan (8 shared papers)Lingfeng Niu (16 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)IEEE Transactions on Network Science and Engineering (1 paper)The Visual Computer (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Minglong Lei
28 papers receiving 371 citations
Peers
Comparison fields: 5 of 79
- Artificial Intelligence 222
- Accounting 56
- Statistical and Nonlinear Physics 42
- Computer Vision and Pattern Recognition 65
- Cognitive Neuroscience 41
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 32 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 74 | |
| 2 | 2022 | 46 | |
| 3 | 2020 | 29 | |
| 4 | 2022 | 21 | |
| 5 | 2018 | 21 | |
| 6 | 2022 | 20 | |
| 7 | 2021 | 17 | |
| 8 | 2022 | 17 | |
| 9 | 2022 | 17 | |
| 10 | 2024 | 14 | |
| 11 | 2023 | 14 | |
| 12 | 2020 | 14 | |
| 13 | 2022 | 12 | |
| 14 | 2019 | 10 | |
| 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 Sociology and Political Science, having authored 32 papers that have together received 384 indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (14 papers), Complex Network Analysis Techniques (10 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 Impact of Technology on Adolescents (2 papers). The work is most often cited by research in Artificial Intelligence (222 citations), Accounting (56 citations), Statistical and Nonlinear Physics (42 citations), Computer Vision and Pattern Recognition (65 citations) and Cognitive Neuroscience (41 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, IEEE Transactions on Network Science and Engineering 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.