Lei Wu
Impact in
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- IoT and Edge/Fog Computing
- Distributed and Parallel Computing Systems
- Nonlinear Dynamics and Pattern Formation
- Information Systems top 2%
- Cloud Computing and Resource Management
- Blockchain Technology Applications and Security
Papers in
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- Cloud Computing and Resource Management 19
- Service-Oriented Architecture and Web Services 16
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- IoT and Edge/Fog Computing 14
- Distributed and Parallel Computing Systems 12
- Software System Performance and Reliability 7
Lei Wu
77 papers receiving 749 citations
Hit Papers
Peers
Comparison fields: 5 of 108
- Computer Networks and Communications 309
- Information Systems 274
- Statistical and Nonlinear Physics 132
- Artificial Intelligence 255
- Industrial and Manufacturing Engineering 66
Countries citing papers authored by Lei Wu
This map shows the geographic impact of Lei Wu'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 Lei Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lei Wu more than expected).
Fields of papers citing papers by Lei Wu
This network shows the impact of papers produced by Lei Wu. 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 Lei Wu. The network helps show where Lei Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Lei Wu, 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 | 3 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 8 | |
| 4 | 2022 | 17 | |
| 5 | The Slow Deterioration of the Generalization Error of the Random Feature Model | 2020 | 1 |
| 6 | Global Convergence of Gradient Descent for Deep Linear Residual Networks | 2019 | 2 |
| 7 | Barron Spaces and the Compositional Function Spaces for Neural Network Models. | 2019 | 27 |
| 8 | Application of 3D Digital Modeling and Virtual Simulation Technology in Ancient Architecture | 2019 | 1 |
| 9 | 2019 | 4 | |
| 10 | 2019 | 13 | |
| 11 | 2019 | 1 | |
| 12 | 2017 | 4 | |
| 13 | 2014 | 11 | |
| 14 | 2012 | 3 | |
| 15 | An intelligent load balancing algorithm towards efficient cloud computing | 2011 | 18 |
| 16 | 2011 | 3 | |
| 17 | 2011 | 10 | |
| 18 | Personalization based on domain ontology | 2006 | 1 |
| 19 | Computational Intelligence Based on Adaptive Control of HVDC System | 2006 | 1 |
| 20 | Program comprehension with dynamic recovery of code collaboration patterns and roles | 2004 | 3 |
About Lei Wu
Lei Wu is a scholar working on Information Systems, Computer Networks and Communications, Artificial Intelligence, Information Systems and Management and Software, having authored 88 papers that have together received 786 indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (19 papers), Service-Oriented Architecture and Web Services (16 papers), IoT and Edge/Fog Computing (14 papers), Distributed and Parallel Computing Systems (12 papers), Advanced Software Engineering Methodologies (9 papers), Neural Networks and Applications (7 papers), Software System Performance and Reliability (7 papers) and Scientific Computing and Data Management (5 papers). The work is most often cited by research in Computer Networks and Communications (309 citations), Information Systems (274 citations), Statistical and Nonlinear Physics (132 citations), Artificial Intelligence (255 citations) and Industrial and Manufacturing Engineering (66 citations). Lei Wu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Shijun Liu, Xiangxu Meng, Jiangping Chen, Junhua Ding, Haihua Chen, Li Pan, Chunlai Li, Wei Lu, E Weinan and Yi Wei. Their work appears in journals such as IEEE Access, Mobile Networks and Applications, Journal of Computational and Nonlinear Dynamics, IEEE Transactions on Neural Networks and Learning Systems and The Electronic Library.
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.