Qing Ping
Impact in
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- Multimodal Machine Learning Applications
- Data Visualization and Analytics
- Generative Adversarial Networks and Image Synthesis
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- scientometrics and bibliometrics research
Papers in
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- Data Visualization and Analytics 3
- Multimodal Machine Learning Applications 3
- Video Analysis and Summarization 1
- Oncology 3
- Cancer survivorship and care 3
- Co-authors
- Chaomei Chen (4 shared papers)Jiangen He (2 shared papers)Prem Natarajan (2 shared papers)Feng Gao (1 shared paper)Nancy E. Avis (3 shared papers)Christopher C. Yang (3 shared papers)Ying Nian Wu (1 shared paper)Edward H. Ip (3 shared papers)
- Journals
- Journal of the Association for Information Science and Technology (2 papers)BMC Bioinformatics (1 paper)Quality of Life Research (1 paper)World Wide Web (1 paper)IEEE Transactions on Computational Social Systems (1 paper)
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Qing Ping
16 papers receiving 319 citations
Peers
Comparison fields: 5 of 81
- Computer Vision and Pattern Recognition 113
- Statistics, Probability and Uncertainty 30
- Artificial Intelligence 64
- Information Systems 30
- Oncology 22
Countries citing papers authored by Qing Ping
This map shows the geographic impact of Qing Ping'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 Qing Ping with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qing Ping more than expected).
Fields of papers citing papers by Qing Ping
This network shows the impact of papers produced by Qing Ping. 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 Qing Ping. The network helps show where Qing Ping may publish in the future.
Co-authors
The 25 scholars most cited alongside Qing Ping, 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 | 2017 | 70 | |
| 2 | 2022 | 58 | |
| 3 | 2015 | 34 | |
| 4 | 2019 | 24 | |
| 5 | 2017 | 22 | |
| 6 | 2016 | 20 | |
| 7 | 2019 | 19 | |
| 8 | 2023 | 19 | |
| 9 | 2017 | 16 | |
| 10 | 2021 | 13 | |
| 11 | 2018 | 12 | |
| 12 | 2018 | 11 | |
| 13 | 2018 | 6 | |
| 14 | 2016 | 4 | |
| 15 | 2015 | 1 | |
| 16 | 2022 | 1 | |
| 17 | 2015 | 0 |
About Qing Ping
Qing Ping is a scholar working on Computer Vision and Pattern Recognition, Oncology, Statistics, Probability and Uncertainty, Artificial Intelligence and Social Psychology, having authored 17 papers that have together received 330 indexed citations. Recurring topics across this work include Data Visualization and Analytics (3 papers), Cancer survivorship and care (3 papers), Multimodal Machine Learning Applications (3 papers), Bioinformatics and Genomic Networks (2 papers), Video Analysis and Summarization (1 paper), Data-Driven Disease Surveillance (1 paper), Recommender Systems and Techniques (1 paper) and Privacy-Preserving Technologies in Data (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (113 citations), Statistics, Probability and Uncertainty (30 citations), Artificial Intelligence (64 citations), Information Systems (30 citations) and Oncology (22 citations). Qing Ping has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Chaomei Chen, Jiangen He, Prem Natarajan, Feng Gao, Nancy E. Avis, Christopher C. Yang, Ying Nian Wu, Edward H. Ip, Bing Wu and Xiwei Tang. Their work appears in journals such as Journal of the Association for Information Science and Technology, BMC Bioinformatics, Quality of Life Research, World Wide Web and IEEE Transactions on Computational Social Systems.
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.