Tianshu Qu
- Cognitive Neuroscience top 10%
- Signal Processing top 5%
- Speech and Hearing top 10%
- Experimental and Cognitive Psychology
- Biomedical Engineering
- Co-authors
- Xihong WuYing HuangXiaodong LiXun ChenLiang LiQiang HuangMing LeiChangming Wang
- Topics
- Speech and Audio Processing (32 papers)Hearing Loss and Rehabilitation (20 papers)Music and Audio Processing (11 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Tianshu Qu
38 papers receiving 280 citations
Peers
Comparison fields: 5 of 50
- Cognitive Neuroscience 202
- Signal Processing 125
- Speech and Hearing 43
- Experimental and Cognitive Psychology 40
- Biomedical Engineering 38
Countries citing papers authored by Tianshu Qu
This map shows the geographic impact of Tianshu Qu'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 Tianshu Qu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tianshu Qu more than expected).
Fields of papers citing papers by Tianshu Qu
This network shows the impact of papers produced by Tianshu Qu. 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 Tianshu Qu. The network helps show where Tianshu Qu may publish in the future.
Co-authorship network of co-authors of Tianshu Qu
This figure shows the co-authorship network connecting the top 25 collaborators of Tianshu Qu. A scholar is included among the top collaborators of Tianshu Qu 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 Tianshu Qu. Tianshu Qu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | Higher order ambisonics compression method based on independent component analysis | 4 |
| 5 | 0 | |
| 6 | 0 | |
| 7 | Sparse Autoencoder Based Multiple Audio Objects Coding Method | 7 |
| 8 | 3 | |
| 9 | High Order Ambisonics Encoding Method Using Differential Microphone Array | 0 |
| 10 | Bandwidth Extension Method Based on Generative Adversarial Nets for Audio Compression | 1 |
| 11 | Subjective Evaluation of Virtual Room Auralization System Based on the Ambisonics Matching Projection Decoding Method | 1 |
| 12 | 6 | |
| 13 | 5 | |
| 14 | 27 | |
| 15 | 10 | |
| 16 | 19 | |
| 17 | 0 | |
| 18 | 5 | |
| 19 | 13 | |
| 20 | 41 |
About Tianshu Qu
Tianshu Qu is a scholar working on Signal Processing, Cognitive Neuroscience and Speech and Hearing, having authored 47 papers that have together received 292 indexed citations. Recurring topics across this work include Speech and Audio Processing (32 papers), Hearing Loss and Rehabilitation (20 papers) and Music and Audio Processing (11 papers). The work is most often cited by research in Signal Processing (125 citations), Cognitive Neuroscience (202 citations) and Speech and Hearing (43 citations). Tianshu Qu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Xihong Wu, Ying Huang, Xiaodong Li, Xun Chen, Liang Li, Qiang Huang, Liang Li, Ming Lei, Changming Wang and Liang Li. Their work appears in journals such as PLoS ONE, The Journal of the Acoustical Society of America and Journal of Cognitive Neuroscience.
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.