Guoqi Qian
- Statistics and Probability top 2%
- Statistical Methods and Inference 16
- Advanced Statistical Methods and Models 9
- Statistical Methods and Bayesian Inference 8
- Artificial Intelligence top 10%
- Bayesian Methods and Mixture Models 12
- Advanced Clustering Algorithms Research 5
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- COVID-19 epidemiological studies 5
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- Fault Detection and Control Systems 5
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- Climate variability and models 5
- Co-authors
- James CuiHans R. KünschYuriy KuleshovJasper S. WijnandsYuehua WuRupesh GuptaAntoinette TordesillasChris Field
- Cited by
- Statistics and ProbabilityManagement Science and Operations ResearchArtificial Intelligence
- Journals
- Proceedings of the National Academy of Sciences (1 paper)SHILAP Revista de lepidopterología (3 papers)IEEE Transactions on Information Theory (2 papers)
In The Last Decade
Guoqi Qian
66 papers receiving 512 citations
Peers
Comparison fields: 5 of 132
- Statistics and Probability 138
- Management Science and Operations Research 65
- Artificial Intelligence 122
- Modeling and Simulation 17
- Atmospheric Science 62
Countries citing papers authored by Guoqi Qian
This map shows the geographic impact of Guoqi Qian'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 Guoqi Qian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guoqi Qian more than expected).
Fields of papers citing papers by Guoqi Qian
This network shows the impact of papers produced by Guoqi Qian. 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 Guoqi Qian. The network helps show where Guoqi Qian may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Guoqi Qian, 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 | 2024 | 4 | |
| 2 | 2024 | 4 | |
| 3 | 2024 | 4 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 8 | |
| 6 | 2023 | 2 | |
| 7 | 2023 | 4 | |
| 8 | 2023 | 4 | |
| 9 | 2022 | 41 | |
| 10 | 2022 | 4 | |
| 11 | 2022 | 7 | |
| 12 | 2021 | 2 | |
| 13 | Bayesian Sparse Global-Local Shrinkage Regression for Grouped Variables | 2017 | 1 |
| 14 | 2016 | 3 | |
| 15 | 2015 | 2 | |
| 16 | Estimation and Selection in Regression Clustering | 2011 | 2 |
| 17 | 2010 | 1 | |
| 18 | Stochastic Complexity, Histograms and Hypothesis Testing of Homogeneity | 2009 | 1 |
| 19 | 2007 | 114 | |
| 20 | STRONG LIMIT THEOREMS ON MODEL SELECTION IN GENERALIZED LINEAR REGRESSION WITH BINOMIAL RESPONSES | 2006 | 4 |
About Guoqi Qian
Guoqi Qian is a scholar working on Statistics and Probability, Modeling and Simulation and Artificial Intelligence, having authored 68 papers that have together received 543 indexed citations. Recurring topics across this work include Statistical Methods and Inference (16 papers), Bayesian Methods and Mixture Models (12 papers), Advanced Statistical Methods and Models (9 papers), Statistical Methods and Bayesian Inference (8 papers), Fault Detection and Control Systems (5 papers), Climate variability and models (5 papers), Advanced Clustering Algorithms Research (5 papers) and COVID-19 epidemiological studies (5 papers). The work is most often cited by research in Statistics and Probability (138 citations), Management Science and Operations Research (65 citations) and Artificial Intelligence (122 citations). Guoqi Qian has collaborated with scholars based in Australia, China and Canada. Frequent co-authors include James Cui, Hans R. Künsch, Yuriy Kuleshov, Jasper S. Wijnands, Yuehua Wu, Rupesh Gupta, Antoinette Tordesillas, Chris Field, Wei Shao and Ning Li. Their work appears in journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and IEEE Transactions on Information Theory.
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.