Guangliang Li
- Ocean Engineering top 1%
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Control and Systems Engineering top 5%
- Molecular Biology
- Topics
- Reinforcement Learning in Robotics (27 papers)Underwater Vehicles and Communication Systems (19 papers)Machine Learning and ELM (9 papers)
- Partner nations
- ChinaJapanNetherlands
In The Last Decade
Guangliang Li
74 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 138
- Ocean Engineering 364
- Computer Vision and Pattern Recognition 334
- Artificial Intelligence 329
- Control and Systems Engineering 261
- Molecular Biology 194
Countries citing papers authored by Guangliang Li
This map shows the geographic impact of Guangliang Li'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 Guangliang Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guangliang Li more than expected).
Fields of papers citing papers by Guangliang Li
This network shows the impact of papers produced by Guangliang Li. 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 Guangliang Li. The network helps show where Guangliang Li may publish in the future.
Co-authorship network of co-authors of Guangliang Li
This figure shows the co-authorship network connecting the top 25 collaborators of Guangliang Li. A scholar is included among the top collaborators of Guangliang Li 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 Guangliang Li. Guangliang Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 13 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 0 | |
| 7 | 3 | |
| 8 | 1 | |
| 9 | 0 | |
| 10 | 1 | |
| 11 | 2 | |
| 12 | 1 | |
| 13 | 4 | |
| 14 | 28 | |
| 15 | Side scan sonar segmentation using deep convolutional neural network | 15 |
| 16 | Fish recognition using convolutional neural network | 18 |
| 17 | Controller design of an autonomous underwater vehicle using ELM-based sliding mode control | 0 |
| 18 | 1 | |
| 19 | Using informative behavior to increase engagement while learning from human reward | 1 |
| 20 | 1 |
About Guangliang Li
Guangliang Li is a scholar working on Artificial Intelligence, Ocean Engineering and Control and Systems Engineering, having authored 83 papers that have together received 1.3k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (27 papers), Underwater Vehicles and Communication Systems (19 papers) and Machine Learning and ELM (9 papers). The work is most often cited by research in Ocean Engineering (364 citations), Computer Vision and Pattern Recognition (334 citations) and Control and Systems Engineering (261 citations). Guangliang Li has collaborated with scholars based in China, Japan and Netherlands. Frequent co-authors include Bo He, Qixin Sha, Bo He, Randy Gómez, Keisuke Nakamura, Hongchuan Jin, Haiqi Lu, Xian Wang, Tianhong Yan and Chen Feng. Their work appears in journals such as Physical Review Letters, PLoS ONE and IEEE Access.
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.