Wenjia Wang
- Molecular Biology
- Artificial Intelligence top 10%
- Computational Theory and Mathematics top 10%
- Statistics, Probability and Uncertainty top 5%
- Pharmacology top 10%
- Co-authors
- Rui TuoBenjamin HaalandChangbao WuDingding WangManman SuYing XinXin JiangManhua Cui
- Topics
- Advanced Multi-Objective Optimization Algorithms (9 papers)Gene expression and cancer classification (6 papers)Probabilistic and Robust Engineering Design (5 papers)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Wenjia Wang
53 papers receiving 484 citations
Peers
Comparison fields: 5 of 123
- Molecular Biology 129
- Artificial Intelligence 104
- Computational Theory and Mathematics 73
- Statistics, Probability and Uncertainty 45
- Pharmacology 44
Countries citing papers authored by Wenjia Wang
This map shows the geographic impact of Wenjia Wang'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 Wenjia Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wenjia Wang more than expected).
Fields of papers citing papers by Wenjia Wang
This network shows the impact of papers produced by Wenjia Wang. 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 Wenjia Wang. The network helps show where Wenjia Wang may publish in the future.
Co-authorship network of co-authors of Wenjia Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Wenjia Wang. A scholar is included among the top collaborators of Wenjia Wang 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 Wenjia Wang. Wenjia Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 5 | |
| 11 | 2 | |
| 12 | 2 | |
| 13 | 6 | |
| 14 | 21 | |
| 15 | 30 | |
| 16 | 8 | |
| 17 | Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network | 6 |
| 18 | Kriging Prediction with Isotropic Matern Correlations: Robustness and Experimental Designs | 9 |
| 19 | 3 | |
| 20 | 80 |
About Wenjia Wang
Wenjia Wang is a scholar working on Computational Theory and Mathematics, Statistics, Probability and Uncertainty and Molecular Medicine, having authored 61 papers that have together received 500 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (9 papers), Gene expression and cancer classification (6 papers) and Probabilistic and Robust Engineering Design (5 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (45 citations), Pharmacology (44 citations) and Computational Theory and Mathematics (73 citations). Wenjia Wang has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Rui Tuo, Benjamin Haaland, Changbao Wu, Dingding Wang, Manman Su, Ying Xin, Xin Jiang, Manhua Cui, Tianmin Xu and Derek Partridge. Their work appears in journals such as Journal of the American Statistical Association, Bioinformatics and Technometrics.
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.