Liang Hu
- Information Systems top 1%
- Artificial Intelligence top 2%
- Computer Networks and Communications top 5%
- Computer Vision and Pattern Recognition top 5%
- Management Science and Operations Research top 5%
- Topics
- Recommender Systems and Techniques (21 papers)Topic Modeling (12 papers)Advanced Graph Neural Networks (7 papers)
- Journals
- SHILAP Revista de lepidopterologíaBioinformaticsIEEE Access
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Liang Hu
59 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 110
- Information Systems 753
- Artificial Intelligence 619
- Computer Networks and Communications 237
- Computer Vision and Pattern Recognition 182
- Management Science and Operations Research 153
Countries citing papers authored by Liang Hu
This map shows the geographic impact of Liang Hu'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 Liang Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liang Hu more than expected).
Fields of papers citing papers by Liang Hu
This network shows the impact of papers produced by Liang Hu. 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 Liang Hu. The network helps show where Liang Hu may publish in the future.
Co-authorship network of co-authors of Liang Hu
This figure shows the co-authorship network connecting the top 25 collaborators of Liang Hu. A scholar is included among the top collaborators of Liang Hu 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 Liang Hu. Liang Hu 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 | 0 | |
| 3 | 1 | |
| 4 | 4 | |
| 5 | 3 | |
| 6 | 8 | |
| 7 | 0 | |
| 8 | 24 | |
| 9 | 13 | |
| 10 | 7 | |
| 11 | 67 | |
| 12 | 32 | |
| 13 | Research on the Internet of Things (IoT) | 2 |
| 14 | 46 | |
| 15 | 25 | |
| 16 | A Survey on Data Migration Management in Cloud Environment | 1 |
| 17 | 24 | |
| 18 | LimeVI: A platform for virtual cluster live migration over WAN. | 1 |
| 19 | Scheme of Electronic Seal Based on IBE and Digital Watermark | 4 |
| 20 | Improvement to Forecasting Algorithms for Performance of Resource in NWS | 0 |
About Liang Hu
Liang Hu is a scholar working on Computational Mathematics, Information Systems and Artificial Intelligence, having authored 69 papers that have together received 1.1k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (21 papers), Topic Modeling (12 papers) and Advanced Graph Neural Networks (7 papers). The work is most often cited by research in Information Systems (753 citations), Artificial Intelligence (619 citations) and Computational Mathematics (11 citations). Liang Hu has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Longbing Cao, Zhiping Gu, Guandong Xu, Jian Cao, Shoujin Wang, Xiaoshui Huang, Can Zhu, Wei Liu, Defu Lian and Jingyan Jiang. Their work appears in journals such as SHILAP Revista de lepidopterología, Bioinformatics 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.