Boshi Wang
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
-
- Topic Modeling
- Natural Language Processing Techniques
- Explainable Artificial Intelligence (XAI)
- Machine Learning in Healthcare
- Semantic Web and Ontologies
Papers in
-
- Topic Modeling 3
- Natural Language Processing Techniques 2
- Domain Adaptation and Few-Shot Learning 2
- Machine Learning and ELM 1
- Co-authors
- Xiang Deng (2 shared papers)Huan Sun (2 shared papers)Sewon Min (1 shared paper)Jiaming Shen (1 shared paper)Luke Zettlemoyer (1 shared paper)Xiang Yue (2 shared papers)Kai Zhang (1 shared paper)Fanglei Shi (1 shared paper)
- Journals
- American Journal of Primatology (1 paper)Electronics (1 paper)Conservation Genetics Resources (1 paper)2022 IEEE International Conference on Big Data (Big Data) (1 paper)Advances in intelligent systems research (1 paper)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Boshi Wang
11 papers receiving 132 citations
Peers
Comparison fields: 5 of 55
- Health Informatics 12
- Artificial Intelligence 87
- General Social Sciences 3
- Computer Vision and Pattern Recognition 16
- Safety Research 6
Countries citing papers authored by Boshi Wang
This map shows the geographic impact of Boshi 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 Boshi Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Boshi Wang more than expected).
Fields of papers citing papers by Boshi Wang
This network shows the impact of papers produced by Boshi 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 Boshi Wang. The network helps show where Boshi Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Boshi Wang, 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 | 2023 | 49 | |
| 2 | 2022 | 39 | |
| 3 | 2015 | 13 | |
| 4 | 2023 | 12 | |
| 5 | 2023 | 12 | |
| 6 | 2020 | 4 | |
| 7 | 2024 | 2 | |
| 8 | 2013 | 2 | |
| 9 | 2022 | 2 | |
| 10 | 2023 | 1 | |
| 11 | 2013 | 1 |
About Boshi Wang
Boshi Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Social Psychology and Political Science and International Relations, having authored 11 papers that have together received 137 indexed citations. Recurring topics across this work include Topic Modeling (3 papers), Natural Language Processing Techniques (2 papers), Genomics and Phylogenetic Studies (2 papers), Primate Behavior and Ecology (2 papers), Domain Adaptation and Few-Shot Learning (2 papers), Machine Learning and ELM (1 paper), COVID-19 diagnosis using AI (1 paper) and Legal Education and Practice Innovations (1 paper). The work is most often cited by research in Health Informatics (12 citations), Artificial Intelligence (87 citations), General Social Sciences (3 citations), Computer Vision and Pattern Recognition (16 citations) and Safety Research (6 citations). Boshi Wang has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Xiang Deng, Huan Sun, Sewon Min, Jiaming Shen, Luke Zettlemoyer, Xiang Yue, Huan Sun, Kai Zhang, Fanglei Shi and Adrian Barbu. Their work appears in journals such as American Journal of Primatology, Electronics, Conservation Genetics Resources, 2022 IEEE International Conference on Big Data (Big Data) and Advances in intelligent systems research.
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.