Xiaowei Xu
- Molecular Biology
- Artificial Intelligence top 5%
- Computational Theory and Mathematics top 2%
- Computer Vision and Pattern Recognition top 5%
- Pharmacology top 5%
- Topics
- Computational Drug Discovery Methods (9 papers)Biomedical Text Mining and Ontologies (6 papers)Domain Adaptation and Few-Shot Learning (5 papers)
- Cited by
- Computational Theory and MathematicsComputer Vision and Pattern RecognitionArtificial Intelligence
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEJournal of Hazardous Materials
- Partner nations
- ChinaUnited StatesIran
In The Last Decade
Xiaowei Xu
54 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 154
- Molecular Biology 349
- Artificial Intelligence 308
- Computational Theory and Mathematics 263
- Computer Vision and Pattern Recognition 211
- Pharmacology 80
Countries citing papers authored by Xiaowei Xu
This map shows the geographic impact of Xiaowei Xu'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 Xiaowei Xu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaowei Xu more than expected).
Fields of papers citing papers by Xiaowei Xu
This network shows the impact of papers produced by Xiaowei Xu. 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 Xiaowei Xu. The network helps show where Xiaowei Xu may publish in the future.
Co-authorship network of co-authors of Xiaowei Xu
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaowei Xu. A scholar is included among the top collaborators of Xiaowei Xu 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 Xiaowei Xu. Xiaowei Xu 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 | 9 | |
| 5 | 14 | |
| 6 | 0 | |
| 7 | 5 | |
| 8 | 4 | |
| 9 | 12 | |
| 10 | 33 | |
| 11 | Uncertainty-Aware Training of Neural Networks for Selective Medical Image Segmentation | 13 |
| 12 | 2 | |
| 13 | 15 | |
| 14 | 33 | |
| 15 | 10 | |
| 16 | 131 | |
| 17 | 56 | |
| 18 | 84 | |
| 19 | 27 | |
| 20 | UALR at TREC: Blog Track. | 5 |
About Xiaowei Xu
Xiaowei Xu is a scholar working on Toxicology, Transportation and Computational Theory and Mathematics, having authored 64 papers that have together received 1.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), Biomedical Text Mining and Ontologies (6 papers) and Domain Adaptation and Few-Shot Learning (5 papers). The work is most often cited by research in Computational Theory and Mathematics (263 citations), Computer Vision and Pattern Recognition (211 citations) and Artificial Intelligence (308 citations). Xiaowei Xu has collaborated with scholars based in China, United States and Iran. Frequent co-authors include Weida Tong, Hong Fang, Gan Sun, Yang Cong, Halil Bişğin, Jiahua Dong, Bineng Zhong, William Slikker, Donna L. Mendrick and Zhichao Liu. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Hazardous Materials.
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.