Ying Wu
- Statistics and Probability top 2%
- Statistical Methods and Inference 7
- Statistical Methods and Bayesian Inference 6
- Media Technology top 5%
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- Advanced Vision and Imaging 3
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- Cancer-related molecular mechanisms research 3
- Rheumatology top 10%
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- Adipokines, Inflammation, and Metabolic Diseases 3
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- Cholangiocarcinoma and Gallbladder Cancer Studies 3
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- Cancer-related gene regulation 3
- Extracellular vesicles in disease 3
- Co-authors
- Jun S. LiuShengyang DaiRichard J. CookVinod ChandranDafna D. GladmanLihi EderRobert M.W. HofstraCharles H.C.M. Buys
- Journals
- Journal of the American Statistical Association (1 paper)The Journal of Clinical Endocrinology & Metabolism (1 paper)Biometrics (1 paper)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Ying Wu
68 papers receiving 975 citations
Peers
Comparison fields: 5 of 145
- Statistics and Probability 243
- Media Technology 79
- Computer Vision and Pattern Recognition 149
- Cancer Research 94
- Rheumatology 83
Countries citing papers authored by Ying Wu
This map shows the geographic impact of Ying Wu'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 Ying Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying Wu more than expected).
Fields of papers citing papers by Ying Wu
This network shows the impact of papers produced by Ying Wu. 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 Ying Wu. The network helps show where Ying Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ying Wu, 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 | 2025 | 1 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2023 | 9 | |
| 8 | 2023 | 21 | |
| 9 | 2023 | 9 | |
| 10 | 2023 | 0 | |
| 11 | 2023 | 2 | |
| 12 | 2022 | 0 | |
| 13 | 2022 | 0 | |
| 14 | 2022 | 5 | |
| 15 | 2022 | 77 | |
| 16 | 2017 | 4 | |
| 17 | 2015 | 83 | |
| 18 | Determinants of U.S. Consumption Expenditures: 1999-2008 | 2014 | 1 |
| 19 | 1999 | 204 | |
| 20 | 1997 | 84 |
About Ying Wu
Ying Wu is a scholar working on Computational Mathematics, Statistics and Probability and Cancer Research, having authored 84 papers that have together received 1.0k indexed citations. Recurring topics across this work include Statistical Methods and Inference (7 papers), Statistical Methods and Bayesian Inference (6 papers), Advanced Vision and Imaging (3 papers), Adipokines, Inflammation, and Metabolic Diseases (3 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (3 papers), Cancer-related molecular mechanisms research (3 papers), Cancer-related gene regulation (3 papers) and Extracellular vesicles in disease (3 papers). The work is most often cited by research in Statistics and Probability (243 citations), Media Technology (79 citations) and Computer Vision and Pattern Recognition (149 citations). Ying Wu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Jun S. Liu, Shengyang Dai, Richard J. Cook, Vinod Chandran, Dafna D. Gladman, Lihi Eder, Robert M.W. Hofstra, Charles H.C.M. Buys, Ray‐Bing Chen and Chi‐Hsiang Chu. Their work appears in journals such as Journal of the American Statistical Association, The Journal of Clinical Endocrinology & Metabolism and Biometrics.
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.