Harrison H. Zhou
- Statistics and Probability top 0.5%
- Statistical Methods and Inference 26
- Statistical Methods and Bayesian Inference 8
- Markov Chains and Monte Carlo Methods 5
- Random Matrices and Applications 4
- Advanced Statistical Methods and Models 4
- Computational Mathematics top 10%
- Artificial Intelligence top 5%
- Bayesian Methods and Mixture Models 9
- Signal Processing top 5%
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- Image and Signal Denoising Methods 6
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- Sparse and Compressive Sensing Techniques 5
Harrison H. Zhou
36 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 108
- Statistics and Probability 634
- Computational Mathematics 13
- Statistical and Nonlinear Physics 175
- Artificial Intelligence 365
- Signal Processing 118
Countries citing papers authored by Harrison H. Zhou
This map shows the geographic impact of Harrison H. 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 Harrison H. Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Harrison H. Zhou more than expected).
Fields of papers citing papers by Harrison H. Zhou
This network shows the impact of papers produced by Harrison H. 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 Harrison H. Zhou. The network helps show where Harrison H. Zhou may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Harrison H. Zhou, 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 | 3 | |
| 3 | 2024 | 0 | |
| 4 | 2022 | 13 | |
| 5 | 2017 | 71 | |
| 6 | Optimal estimation and completion of matrices with biclustering structures | 2016 | 19 |
| 7 | 2016 | 97 | |
| 8 | 2016 | 3 | |
| 9 | 2016 | 100 | |
| 10 | 2015 | 30 | |
| 11 | 2015 | 39 | |
| 12 | 2015 | 15 | |
| 13 | A DATA-DRIVEN BLOCK THRESHOLDING APPROACH TO WAVELET ESTIMATION | 2013 | 39 |
| 14 | ROBUST NONPARAMETRIC ESTIMATION VIA WAVELET MEDIAN REGRESSION | 2012 | 16 |
| 15 | 2012 | 49 | |
| 16 | 2010 | 0 | |
| 17 | FUNCTIONAL REGRESSION FOR GENERAL EXPONENTIAL FAMILIES | 2010 | 1 |
| 18 | 2010 | 26 | |
| 19 | 2009 | 43 | |
| 20 | 2009 | 17 |
About Harrison H. Zhou
Harrison H. Zhou is a scholar working on Statistics and Probability, Structural Biology and Finance, having authored 40 papers that have together received 1.2k indexed citations. Recurring topics across this work include Statistical Methods and Inference (26 papers), Bayesian Methods and Mixture Models (9 papers), Statistical Methods and Bayesian Inference (8 papers), Image and Signal Denoising Methods (6 papers), Sparse and Compressive Sensing Techniques (5 papers), Markov Chains and Monte Carlo Methods (5 papers), Random Matrices and Applications (4 papers) and Advanced Statistical Methods and Models (4 papers). The work is most often cited by research in Statistics and Probability (634 citations), Computational Mathematics (13 citations) and Statistical and Nonlinear Physics (175 citations). Harrison H. Zhou has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Tommaso Cai, Zhao Ren, Chao Gao, Zongming Ma, Hongyu Zhao, Weidong Liu, Chao Gao, Yu Lu, Cun‐Hui Zhang and Tingni Sun. Their work appears in journals such as Journal of the American Statistical Association, Monthly Notices of the Royal Astronomical Society 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.