Qinghua Liu
- Artificial Intelligence top 10%
- Signal Processing
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Co-authors
- Gauri JoshiJianyu WangHao LiangH. Vincent PoorYing XiongFei HanQing-Hua LingJohn Paparrizos
- Topics
- Time Series Analysis and Forecasting (5 papers)Anomaly Detection Techniques and Applications (5 papers)Network Security and Intrusion Detection (3 papers)
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Qinghua Liu
21 papers receiving 211 citations
Peers
Comparison fields: 5 of 74
- Artificial Intelligence 101
- Signal Processing 30
- Computer Networks and Communications 30
- Computer Vision and Pattern Recognition 28
- Electrical and Electronic Engineering 23
Countries citing papers authored by Qinghua Liu
This map shows the geographic impact of Qinghua Liu'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 Qinghua Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qinghua Liu more than expected).
Fields of papers citing papers by Qinghua Liu
This network shows the impact of papers produced by Qinghua Liu. 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 Qinghua Liu. The network helps show where Qinghua Liu may publish in the future.
Co-authorship network of co-authors of Qinghua Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Qinghua Liu. A scholar is included among the top collaborators of Qinghua Liu 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 Qinghua Liu. Qinghua Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 13 | |
| 5 | 1 | |
| 6 | 16 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 71 | |
| 11 | A Joint Allocation Algorithm of Computing and Communication Resources Based on Reinforcement Learning in MEC System | 1 |
| 12 | Provable Rich Observation Reinforcement Learning with Combinatorial Latent States | 2 |
| 13 | A Sharp Analysis of Model-based Reinforcement Learning with Self-Play | 1 |
| 14 | 6 | |
| 15 | 8 | |
| 16 | 27 | |
| 17 | 17 | |
| 18 | 9 | |
| 19 | 8 | |
| 20 | 7 |
About Qinghua Liu
Qinghua Liu is a scholar working on Signal Processing, Artificial Intelligence and Computer Networks and Communications, having authored 22 papers that have together received 214 indexed citations. Recurring topics across this work include Time Series Analysis and Forecasting (5 papers), Anomaly Detection Techniques and Applications (5 papers) and Network Security and Intrusion Detection (3 papers). The work is most often cited by research in Artificial Intelligence (101 citations), Signal Processing (30 citations) and Computer Science Applications (11 citations). Qinghua Liu has collaborated with scholars based in China, United States and France. Frequent co-authors include Gauri Joshi, Jianyu Wang, Hao Liang, H. Vincent Poor, Ying Xiong, Fei Han, Qing-Hua Ling, John Paparrizos, Paul Boniol and Themis Palpanas. Their work appears in journals such as IEEE Transactions on Signal Processing, Optics Express and BMC Bioinformatics.
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.