Hui Guan
- Mechanics of Materials top 10%
- Artificial Intelligence top 10%
- Ocean Engineering top 5%
- Mechanical Engineering
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Baowei WangXipeng ShenNaixue XiongK. S. SorbieK. J. PackerDermot F. BroughamMarco SerafiniYang Shen
- Topics
- Software Engineering Research (9 papers)Advanced Neural Network Applications (9 papers)Hydrocarbon exploration and reservoir analysis (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaCommunications of the ACMOptics Express
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Hui Guan
68 papers receiving 496 citations
Peers
Comparison fields: 5 of 88
- Mechanics of Materials 140
- Artificial Intelligence 132
- Ocean Engineering 102
- Mechanical Engineering 99
- Computer Vision and Pattern Recognition 86
Countries citing papers authored by Hui Guan
This map shows the geographic impact of Hui Guan'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 Hui Guan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hui Guan more than expected).
Fields of papers citing papers by Hui Guan
This network shows the impact of papers produced by Hui Guan. 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 Hui Guan. The network helps show where Hui Guan may publish in the future.
Co-authorship network of co-authors of Hui Guan
This figure shows the co-authorship network connecting the top 25 collaborators of Hui Guan. A scholar is included among the top collaborators of Hui Guan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hui Guan. Hui Guan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 7 | |
| 6 | 1 | |
| 7 | 14 | |
| 8 | 4 | |
| 9 | 1 | |
| 10 | 2 | |
| 11 | FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks. | 2 |
| 12 | 9 | |
| 13 | 8 | |
| 14 | 32 | |
| 15 | 6 | |
| 16 | 3 | |
| 17 | Practical Research on Brand Image and Its Effects on Consumers Behavior Intension | 1 |
| 18 | 1 | |
| 19 | 6 | |
| 20 | Source of Natural Gas and Gas Reservoir Formation Stage in Mandong-Yingjisu Area | 1 |
About Hui Guan
Hui Guan is a scholar working on Software, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 75 papers that have together received 521 indexed citations. Recurring topics across this work include Software Engineering Research (9 papers), Advanced Neural Network Applications (9 papers) and Hydrocarbon exploration and reservoir analysis (8 papers). The work is most often cited by research in Ocean Engineering (102 citations), Mechanics of Materials (140 citations) and Hardware and Architecture (37 citations). Hui Guan has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Baowei Wang, Xipeng Shen, Naixue Xiong, K. S. Sorbie, K. J. Packer, Dermot F. Brougham, Marco Serafini, Yang Shen, Hongji Yang and Fudong Zhang. Their work appears in journals such as SHILAP Revista de lepidopterología, Communications of the ACM and Optics Express.
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.