Zuofeng Shang
- Statistics and Probability top 2%
- Artificial Intelligence top 10%
- Economics and Econometrics
- Molecular Biology
- Statistical and Nonlinear Physics
- Co-authors
- Guang ChengMurray K. ClaytonGanggang XuYang FengChunming ZhangGuanqun CaoYuan JiangYonghui Zhang
- Topics
- Statistical Methods and Inference (25 papers)Statistical Methods and Bayesian Inference (8 papers)Advanced Statistical Methods and Models (8 papers)
- Journals
- Journal of the American Statistical AssociationIEEE Transactions on Pattern Analysis and Machine IntelligenceJournal of Econometrics
- Partner nations
- United StatesChinaNetherlands
In The Last Decade
Zuofeng Shang
37 papers receiving 294 citations
Peers
Comparison fields: 5 of 58
- Statistics and Probability 185
- Artificial Intelligence 93
- Economics and Econometrics 38
- Molecular Biology 32
- Statistical and Nonlinear Physics 31
Countries citing papers authored by Zuofeng Shang
This map shows the geographic impact of Zuofeng Shang'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 Zuofeng Shang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zuofeng Shang more than expected).
Fields of papers citing papers by Zuofeng Shang
This network shows the impact of papers produced by Zuofeng Shang. 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 Zuofeng Shang. The network helps show where Zuofeng Shang may publish in the future.
Co-authorship network of co-authors of Zuofeng Shang
This figure shows the co-authorship network connecting the top 25 collaborators of Zuofeng Shang. A scholar is included among the top collaborators of Zuofeng Shang 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 Zuofeng Shang. Zuofeng Shang 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 | 6 | |
| 5 | 10 | |
| 6 | 3 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | Probabilistic Connection Importance Inference and Lossless Compression of Deep Neural Networks | 1 |
| 10 | Non-asymptotic Analysis for Nonparametric Testing | 2 |
| 11 | Sharp Theoretical Analysis for Nonparametric Testing under Random Projection | 1 |
| 12 | 7 | |
| 13 | 2 | |
| 14 | Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data | 11 |
| 15 | 14 | |
| 16 | 32 | |
| 17 | 3 | |
| 18 | 8 | |
| 19 | 6 | |
| 20 | 5 |
About Zuofeng Shang
Zuofeng Shang is a scholar working on Statistics and Probability, Computational Mathematics and Artificial Intelligence, having authored 40 papers that have together received 313 indexed citations. Recurring topics across this work include Statistical Methods and Inference (25 papers), Statistical Methods and Bayesian Inference (8 papers) and Advanced Statistical Methods and Models (8 papers). The work is most often cited by research in Statistics and Probability (185 citations), Computational Mathematics (6 citations) and Artificial Intelligence (93 citations). Zuofeng Shang has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Guang Cheng, Murray K. Clayton, Ganggang Xu, Yang Feng, Chunming Zhang, Guanqun Cao, Yuan Jiang, Yonghui Zhang, Pang Du and Qiankun Zhou. Their work appears in journals such as Journal of the American Statistical Association, IEEE Transactions on Pattern Analysis and Machine Intelligence and Journal of Econometrics.
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.