Guangyan Huang
- Artificial Intelligence top 5%
- Information Systems top 2%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 5%
- Signal Processing top 5%
- Topics
- Recommender Systems and Techniques (11 papers)Energy Efficient Wireless Sensor Networks (10 papers)Time Series Analysis and Forecasting (9 papers)
- Partner nations
- AustraliaChinaUnited States
In The Last Decade
Guangyan Huang
93 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 131
- Artificial Intelligence 443
- Information Systems 399
- Computer Vision and Pattern Recognition 296
- Computer Networks and Communications 256
- Signal Processing 119
Countries citing papers authored by Guangyan Huang
This map shows the geographic impact of Guangyan Huang'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 Guangyan Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guangyan Huang more than expected).
Fields of papers citing papers by Guangyan Huang
This network shows the impact of papers produced by Guangyan Huang. 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 Guangyan Huang. The network helps show where Guangyan Huang may publish in the future.
Co-authorship network of co-authors of Guangyan Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Guangyan Huang. A scholar is included among the top collaborators of Guangyan Huang 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 Guangyan Huang. Guangyan Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 2 | |
| 3 | 3 | |
| 4 | 3 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 4 | |
| 8 | 17 | |
| 9 | 2 | |
| 10 | 3 | |
| 11 | 75 | |
| 12 | 17 | |
| 13 | 25 | |
| 14 | 44 | |
| 15 | 26 | |
| 16 | DoSTra: Discovering Common Behaviors of Objects Using the Duration of Staying on Each Location of Trajectories | 3 |
| 17 | A Clustering-based Link Prediction Method in Social Networks. | 5 |
| 18 | Current and future development of big data in Commonwealth countries | 2 |
| 19 | 1 | |
| 20 | 4 |
About Guangyan Huang
Guangyan Huang is a scholar working on Computational Mathematics, Signal Processing and Information Systems, having authored 97 papers that have together received 1.4k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (11 papers), Energy Efficient Wireless Sensor Networks (10 papers) and Time Series Analysis and Forecasting (9 papers). The work is most often cited by research in Information Systems (399 citations), Computer Vision and Pattern Recognition (296 citations) and Artificial Intelligence (443 citations). Guangyan Huang has collaborated with scholars based in Australia, China and United States. Frequent co-authors include Jing He, Yanchun Zhang, Borui Cai, Guanghui Li, Najmeh Samadiani, Xun Zhou, Xiangmin Zhou, Yong Xiang, Xiaowei Li and Wei Luo. Their work appears in journals such as PLoS ONE, Expert Systems with Applications 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.