Shuheng Zhou
- Artificial Intelligence top 5%
- Statistics and Probability top 1%
- Computer Networks and Communications top 10%
- Computational Mechanics top 10%
- Computational Theory and Mathematics top 5%
- Co-authors
- Larry WassermanJohn LaffertyMark RudelsonPeter BühlmannSara van de GeerBruce M. MaggsAnupam GuptaSatish Rao
- Topics
- Statistical Methods and Inference (14 papers)Sparse and Compressive Sensing Techniques (7 papers)Bayesian Methods and Mixture Models (6 papers)
- Journals
- Journal of the American Statistical AssociationIEEE Transactions on Information TheoryIEEE Transactions on Signal Processing
- Partner nations
- United StatesSwitzerlandChina
In The Last Decade
Shuheng Zhou
37 papers receiving 802 citations
Peers
Comparison fields: 5 of 97
- Artificial Intelligence 372
- Statistics and Probability 263
- Computer Networks and Communications 143
- Computational Mechanics 122
- Computational Theory and Mathematics 89
Countries citing papers authored by Shuheng Zhou
This map shows the geographic impact of Shuheng Zhou'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 Shuheng Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuheng Zhou more than expected).
Fields of papers citing papers by Shuheng Zhou
This network shows the impact of papers produced by Shuheng Zhou. 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 Shuheng Zhou. The network helps show where Shuheng Zhou may publish in the future.
Co-authorship network of co-authors of Shuheng Zhou
This figure shows the co-authorship network connecting the top 25 collaborators of Shuheng Zhou. A scholar is included among the top collaborators of Shuheng Zhou 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 Shuheng Zhou. Shuheng Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 5 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 8 | |
| 10 | Time-dependent spatially varying graphical models, with application to brain fMRI data analysis | 1 |
| 11 | 6 | |
| 12 | 11 | |
| 13 | The Bigraphical Lasso | 3 |
| 14 | 36 | |
| 15 | 56 | |
| 16 | Prediction and variable selection with the adaptive Lasso | 4 |
| 17 | 6 | |
| 18 | 7 | |
| 19 | Routing, disjoint paths, and classification | 2 |
| 20 | 61 |
About Shuheng Zhou
Shuheng Zhou is a scholar working on Statistics and Probability, Computer Graphics and Computer-Aided Design and Discrete Mathematics and Combinatorics, having authored 41 papers that have together received 852 indexed citations. Recurring topics across this work include Statistical Methods and Inference (14 papers), Sparse and Compressive Sensing Techniques (7 papers) and Bayesian Methods and Mixture Models (6 papers). The work is most often cited by research in Statistics and Probability (263 citations), Computational Mathematics (8 citations) and Artificial Intelligence (372 citations). Shuheng Zhou has collaborated with scholars based in United States, Switzerland and China. Frequent co-authors include Larry Wasserman, John Lafferty, Larry Wasserman, Mark Rudelson, Peter Bühlmann, Sara van de Geer, Bruce M. Maggs, Anupam Gupta, Satish Rao and Theodoros Tsiligkaridis. Their work appears in journals such as Journal of the American Statistical Association, IEEE Transactions on Information Theory and IEEE Transactions on Signal Processing.
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.