J. Weng
Impact in
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- Ethics and Social Impacts of AI
Papers in
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- Adversarial Robustness in Machine Learning 2
- Co-authors
- Stefan Brünner (3 shared papers)M. Á. Aloy (1 shared paper)F.-P. Schilling (2 shared papers)M. Zanetti (1 shared paper)S. Orlando (1 shared paper)M. Miceli (1 shared paper)A. De Roeck (1 shared paper)M. Stavrianakou (1 shared paper)
- Journals
- Journal of Hydrology (1 paper)Astronomy and Astrophysics (1 paper)Annals of Oncology (1 paper)IEEE Symposium Conference Record Nuclear Science 2004. (1 paper)Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences) (2 papers)
- Partner nations
- SwitzerlandChinaAustralia
In The Last Decade
J. Weng
6 papers receiving 10 citations
Peers
Comparison fields: 5 of 16
- Health Informatics 1
- Safety Research 3
- Nuclear and High Energy Physics 4
- Automotive Engineering 2
- Radiation 1
Countries citing papers authored by J. Weng
This map shows the geographic impact of J. Weng'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 J. Weng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Weng more than expected).
Fields of papers citing papers by J. Weng
This network shows the impact of papers produced by J. Weng. 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 J. Weng. The network helps show where J. Weng may publish in the future.
Co-authors
The 25 scholars most cited alongside J. Weng, 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 | 2005 | 3 | |
| 2 | 2023 | 2 | |
| 3 | 2023 | 2 | |
| 4 | 2024 | 2 | |
| 5 | 2025 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2022 | 1 | |
| 8 | DESIGN OF 1.2 GEV SCL AS NEW INJECTOR FOR THE BNL AGS. | 2003 | 1 |
| 9 | 2025 | 0 |
About J. Weng
J. Weng is a scholar working on Artificial Intelligence, Automotive Engineering, Astronomy and Astrophysics, Computer Vision and Pattern Recognition and Health Informatics, having authored 9 papers that have together received 13 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (2 papers), Particle Detector Development and Performance (1 paper), Stellar, planetary, and galactic studies (1 paper), Blood disorders and treatments (1 paper), Ethics and Social Impacts of AI (1 paper), Superconducting Materials and Applications (1 paper), Artificial Intelligence in Healthcare and Education (1 paper) and Acute Myeloid Leukemia Research (1 paper). The work is most often cited by research in Health Informatics (1 citation), Safety Research (3 citations), Nuclear and High Energy Physics (4 citations), Automotive Engineering (2 citations) and Radiation (1 citation). J. Weng has collaborated with scholars based in Switzerland, China and Australia. Frequent co-authors include Stefan Brünner, M. Á. Aloy, F.-P. Schilling, M. Zanetti, S. Orlando, M. Miceli, A. De Roeck, M. Stavrianakou, S.-H. Lee and Shigehiro Nagataki. Their work appears in journals such as Journal of Hydrology, Astronomy and Astrophysics, Annals of Oncology, IEEE Symposium Conference Record Nuclear Science 2004. and Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences).
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.