Binqing Wu
Impact in
- Bioengineering top 10%
- Analytical Chemistry and Sensors
- Signal Processing top 10%
- Time Series Analysis and Forecasting
Papers in
-
- Advanced Fiber Optic Sensors 7
- Photonic and Optical Devices 4
-
- Advanced Fiber Laser Technologies 2
- Mechanical and Optical Resonators 2
- Co-authors
- Chunliu Zhao (7 shared papers)Ben Xu (2 shared papers)Yina Li (1 shared paper)Ling Chen (4 shared papers)Wei Zhang (1 shared paper)Donghui Chen (1 shared paper)Bo Wen (1 shared paper)D. N. Wang (2 shared papers)
- Journals
- ACM Transactions on Knowledge Discovery from Data (1 paper)IEEE Transactions on Cybernetics (1 paper)Optical Fiber Technology (1 paper)Sensors and Actuators B Chemical (1 paper)Journal of Lightwave Technology (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Binqing Wu
12 papers receiving 252 citations
Binqing Wu's Hit Papers
Peers
Comparison fields: 5 of 54
- Bioengineering 39
- Signal Processing 53
- Management Science and Operations Research 35
- Electrical and Electronic Engineering 150
- Building and Construction 24
Countries citing papers authored by Binqing Wu
This map shows the geographic impact of Binqing Wu'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 Binqing Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Binqing Wu more than expected).
Fields of papers citing papers by Binqing Wu
This network shows the impact of papers produced by Binqing Wu. 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 Binqing Wu. The network helps show where Binqing Wu may publish in the future.
Co-authors
The 22 scholars most cited alongside Binqing Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 97 | |
| 2 | Multi-Scale Adaptive Graph Neural Network for Multivariate Time Series Forecasting Hit paper breakdown → | 2023 | 96 |
| 3 | 2023 | 28 | |
| 4 | 2017 | 17 | |
| 5 | 2019 | 11 | |
| 6 | 2017 | 4 | |
| 7 | 2023 | 3 | |
| 8 | 2017 | 3 | |
| 9 | 2019 | 2 | |
| 10 | 2019 | 2 | |
| 11 | 2016 | 1 | |
| 12 | 2016 | 1 | |
| 13 | 2025 | 0 | |
| 14 | 2024 | 0 |
About Binqing Wu
Binqing Wu is a scholar working on Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics, Health, Toxicology and Mutagenesis, Signal Processing and Atmospheric Science, having authored 14 papers that have together received 265 indexed citations. Recurring topics across this work include Advanced Fiber Optic Sensors (7 papers), Photonic and Optical Devices (4 papers), Advanced Chemical Sensor Technologies (2 papers), Time Series Analysis and Forecasting (2 papers), Air Quality Monitoring and Forecasting (2 papers), Advanced Fiber Laser Technologies (2 papers), Mechanical and Optical Resonators (2 papers) and Traffic Prediction and Management Techniques (2 papers). The work is most often cited by research in Bioengineering (39 citations), Signal Processing (53 citations), Management Science and Operations Research (35 citations), Electrical and Electronic Engineering (150 citations) and Building and Construction (24 citations). Binqing Wu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Chunliu Zhao, Ben Xu, Yina Li, Ling Chen, Wei Zhang, Donghui Chen, Bo Wen, D. N. Wang, Juan Kang and Chi Chiu Chan. Their work appears in journals such as ACM Transactions on Knowledge Discovery from Data, IEEE Transactions on Cybernetics, Optical Fiber Technology, Sensors and Actuators B Chemical and Journal of Lightwave Technology.
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.