Lie Wang
- Computational Mechanics top 2%
- Statistics and Probability top 1%
- Biomedical Engineering
- Signal Processing top 5%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Tommaso CaiGuangwu XuVictor ChernozhukovAlexandre BelloniHan LiuTuo ZhaoLawrence D. BrownMichael Levine
- Topics
- Sparse and Compressive Sensing Techniques (9 papers)Statistical Methods and Inference (8 papers)Blind Source Separation Techniques (5 papers)
- Journals
- IEEE Transactions on Information TheoryIEEE Transactions on Signal ProcessingThe Annals of Statistics
- Partner nations
- United StatesChinaCanada
In The Last Decade
Lie Wang
21 papers receiving 751 citations
Peers
Comparison fields: 5 of 96
- Computational Mechanics 439
- Statistics and Probability 295
- Biomedical Engineering 191
- Signal Processing 162
- Computer Vision and Pattern Recognition 103
Countries citing papers authored by Lie Wang
This map shows the geographic impact of Lie Wang'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 Lie Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lie Wang more than expected).
Fields of papers citing papers by Lie Wang
This network shows the impact of papers produced by Lie Wang. 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 Lie Wang. The network helps show where Lie Wang may publish in the future.
Co-authorship network of co-authors of Lie Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Lie Wang. A scholar is included among the top collaborators of Lie Wang 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 Lie Wang. Lie Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 7 | |
| 3 | 1 | |
| 4 | 38 | |
| 5 | 3 | |
| 6 | 55 | |
| 7 | 8 | |
| 8 | 47 | |
| 9 | 98 | |
| 10 | The L[subscript 1] penalized LAD estimator for high dimensional linear regression | 1 |
| 11 | ADAPTIVE VARIANCE FUNCTION ESTIMATION IN HETEROSCEDASTIC NONPARAMETRIC REGRESSION | 27 |
| 12 | 1 | |
| 13 | 47 | |
| 14 | 36 | |
| 15 | PIVOTAL ESTIMATION OF NONPARAMETRIC FUNCTIONS VIA SQUARE-ROOT LASSO | 1 |
| 16 | 110 | |
| 17 | 149 | |
| 18 | 127 | |
| 19 | 1 | |
| 20 | 29 |
About Lie Wang
Lie Wang is a scholar working on Statistics and Probability, Signal Processing and Computational Mechanics, having authored 21 papers that have together received 802 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (9 papers), Statistical Methods and Inference (8 papers) and Blind Source Separation Techniques (5 papers). The work is most often cited by research in Statistics and Probability (295 citations), Acoustics and Ultrasonics (26 citations) and Computational Mechanics (439 citations). Lie Wang has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Tommaso Cai, Guangwu Xu, Victor Chernozhukov, Alexandre Belloni, Han Liu, Tuo Zhao, Lawrence D. Brown, Han Liu, Michael Levine and Wenhua Wang. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing and The Annals of Statistics.
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.