Wei Dai
Impact in
- Acoustics and Ultrasonics top 2%
- Computational Mechanics top 0.2%
- Sparse and Compressive Sensing Techniques
Papers in
-
- Blind Source Separation Techniques 35
-
- Sparse and Compressive Sensing Techniques 68
- Co-authors
- Olgica MilenkovićWenwu WangLinglong DaiZhaocheng WangZhen GaoVincent K. N. LauByonghyo ShimTao Xu
- Journals
- IEEE Transactions on Signal Processing (11 papers)IEEE Transactions on Information Theory (6 papers)IEEE Transactions on Wireless Communications (3 papers)IEEE Journal on Selected Areas in Communications (2 papers)IEEE Transactions on Communications (2 papers)
- Partner nations
- United KingdomUnited StatesChina
In The Last Decade
Wei Dai
97 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 86
- Acoustics and Ultrasonics 114
- Computational Mechanics 2.0k
- Signal Processing 928
- Computational Mathematics 23
- Computer Vision and Pattern Recognition 632
Countries citing papers authored by Wei Dai
This map shows the geographic impact of Wei Dai'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 Wei Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Dai more than expected).
Fields of papers citing papers by Wei Dai
This network shows the impact of papers produced by Wei Dai. 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 Wei Dai. The network helps show where Wei Dai may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Wei Dai, 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 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 9 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 0 | |
| 6 | 2023 | 1 | |
| 7 | 2021 | 12 | |
| 8 | 2021 | 3 | |
| 9 | 2021 | 2 | |
| 10 | 2020 | 1 | |
| 11 | 2018 | 5 | |
| 12 | 2017 | 3 | |
| 13 | On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System | 2016 | 14 |
| 14 | 2015 | 168 | |
| 15 | 2014 | 5 | |
| 16 | Hierarchical Bayesian Kalman filters for wireless sensor networks | 2013 | 1 |
| 17 | 2013 | 2 | |
| 18 | 2010 | 39 | |
| 19 | 2009 | 23 | |
| 20 | Subspace Pursuit for Compressive Sensing Signal Reconstruction Hit paper breakdown → | 2009 | 1667 |
About Wei Dai
Wei Dai is a scholar working on Signal Processing, Computational Mechanics, Computer Networks and Communications, Computer Vision and Pattern Recognition and Instrumentation, having authored 111 papers that have together received 3.2k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (68 papers), Blind Source Separation Techniques (35 papers), Microwave Imaging and Scattering Analysis (15 papers), Image and Signal Denoising Methods (14 papers), Advanced MIMO Systems Optimization (14 papers), Distributed Sensor Networks and Detection Algorithms (13 papers), Photoacoustic and Ultrasonic Imaging (10 papers) and Cooperative Communication and Network Coding (10 papers). The work is most often cited by research in Acoustics and Ultrasonics (114 citations), Computational Mechanics (2.0k citations), Signal Processing (928 citations), Computational Mathematics (23 citations) and Computer Vision and Pattern Recognition (632 citations). Wei Dai has collaborated with scholars based in United Kingdom, United States and China. Frequent co-authors include Olgica Milenković, Wenwu Wang, Linglong Dai, Zhaocheng Wang, Zhen Gao, Vincent K. N. Lau, Byonghyo Shim, Tao Xu, Hoa V. Pham and Youjian Liu. Their work appears in journals such as IEEE Transactions on Signal Processing, IEEE Transactions on Information Theory, IEEE Transactions on Wireless Communications, IEEE Journal on Selected Areas in Communications and IEEE Transactions on Communications.
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.