Yada Zhu
- Artificial Intelligence top 10%
- Management Science and Operations Research top 5%
- Safety, Risk, Reliability and Quality top 5%
- Statistics, Probability and Uncertainty top 5%
- Statistics and Probability top 5%
- Topics
- Stock Market Forecasting Methods (8 papers)Advanced Graph Neural Networks (7 papers)Reliability and Maintenance Optimization (7 papers)
- Cited by
- Management Science and Operations ResearchStatistics, Probability and UncertaintyComputational Mathematics
- Journals
- TechnometricsEuropean Journal of Operational ResearchIEEE Transactions on Knowledge and Data Engineering
- Partner nations
- United StatesChinaNetherlands
In The Last Decade
Yada Zhu
48 papers receiving 468 citations
Peers
Comparison fields: 5 of 74
- Artificial Intelligence 191
- Management Science and Operations Research 133
- Safety, Risk, Reliability and Quality 77
- Statistics, Probability and Uncertainty 73
- Statistics and Probability 61
Countries citing papers authored by Yada Zhu
This map shows the geographic impact of Yada Zhu'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 Yada Zhu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yada Zhu more than expected).
Fields of papers citing papers by Yada Zhu
This network shows the impact of papers produced by Yada Zhu. 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 Yada Zhu. The network helps show where Yada Zhu may publish in the future.
Co-authorship network of co-authors of Yada Zhu
This figure shows the co-authorship network connecting the top 25 collaborators of Yada Zhu. A scholar is included among the top collaborators of Yada Zhu 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 Yada Zhu. Yada Zhu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 4 | |
| 5 | 1 | |
| 6 | 6 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | 7 | |
| 10 | 0 | |
| 11 | 4 | |
| 12 | 12 | |
| 13 | 28 | |
| 14 | 25 | |
| 15 | 1 | |
| 16 | 2 | |
| 17 | 3 | |
| 18 | 11 | |
| 19 | 22 | |
| 20 | 11 |
About Yada Zhu
Yada Zhu is a scholar working on Computational Mathematics, Safety, Risk, Reliability and Quality and Statistics, Probability and Uncertainty, having authored 51 papers that have together received 486 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (8 papers), Advanced Graph Neural Networks (7 papers) and Reliability and Maintenance Optimization (7 papers). The work is most often cited by research in Management Science and Operations Research (133 citations), Statistics, Probability and Uncertainty (73 citations) and Computational Mathematics (5 citations). Yada Zhu has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Jingrui He, Elsayed A. Elsayed, Hanghang Tong, Бо Ли, Hengzhi Pei, Yunan Ye, Boxin Wang, Xiao Ju, Pin‐Yu Chen and Dzung T. Phan. Their work appears in journals such as Technometrics, European Journal of Operational Research and IEEE Transactions on Knowledge and Data Engineering.
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.