Xingxing Liang
- Electrical and Electronic Engineering top 10%
- Automotive Engineering top 5%
- Artificial Intelligence top 10%
- Electronic, Optical and Magnetic Materials
- Computer Networks and Communications top 10%
- Co-authors
- Ying YangXin JinXu WangJincai HuangXin XuDawei ZhaoQiguang MiaoSen Wang
- Topics
- Reinforcement Learning in Robotics (6 papers)Complex Network Analysis Techniques (5 papers)RNA Interference and Gene Delivery (4 papers)
- Cited by
- Automotive EngineeringElectrical and Electronic EngineeringElectronic, Optical and Magnetic Materials
- Journals
- SHILAP Revista de lepidopterologíaDiabetesJournal of Agricultural and Food Chemistry
In The Last Decade
Xingxing Liang
41 papers receiving 853 citations
Hit Papers
Peers
Comparison fields: 5 of 129
- Electrical and Electronic Engineering 344
- Automotive Engineering 195
- Artificial Intelligence 135
- Electronic, Optical and Magnetic Materials 98
- Computer Networks and Communications 80
Countries citing papers authored by Xingxing Liang
This map shows the geographic impact of Xingxing Liang'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 Xingxing Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xingxing Liang more than expected).
Fields of papers citing papers by Xingxing Liang
This network shows the impact of papers produced by Xingxing Liang. 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 Xingxing Liang. The network helps show where Xingxing Liang may publish in the future.
Co-authorship network of co-authors of Xingxing Liang
This figure shows the co-authorship network connecting the top 25 collaborators of Xingxing Liang. A scholar is included among the top collaborators of Xingxing Liang 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 Xingxing Liang. Xingxing Liang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 7 | |
| 9 | 13 | |
| 10 | 0 | |
| 11 | 10 | |
| 12 | 6 | |
| 13 | Deep Reinforcement Learning: A Surveybreakdown → | 340 |
| 14 | 1 | |
| 15 | 9 | |
| 16 | 3 | |
| 17 | 20 | |
| 18 | 17 | |
| 19 | 0 | |
| 20 | 10 |
About Xingxing Liang
Xingxing Liang is a scholar working on Statistics, Probability and Uncertainty, Statistical and Nonlinear Physics and Artificial Intelligence, having authored 49 papers that have together received 877 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (6 papers), Complex Network Analysis Techniques (5 papers) and RNA Interference and Gene Delivery (4 papers). The work is most often cited by research in Automotive Engineering (195 citations), Electrical and Electronic Engineering (344 citations) and Electronic, Optical and Magnetic Materials (98 citations). Xingxing Liang has collaborated with scholars based in China and Germany. Frequent co-authors include Ying Yang, Xin Jin, Xu Wang, Jincai Huang, Xin Xu, Dawei Zhao, Qiguang Miao, Sen Wang, Bin Dai and Feiyu Kang. Their work appears in journals such as SHILAP Revista de lepidopterología, Diabetes and Journal of Agricultural and Food Chemistry.
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.