Quan Gan
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Materials Chemistry
- Aerospace Engineering
- Radiation top 10%
- Co-authors
- Zheng ZhangMinjie WangDa ZhengQipeng GuoZihao YeJinyang LiYu GaiChao Ma
- Topics
- Nuclear reactor physics and engineering (12 papers)Nuclear Physics and Applications (12 papers)Radiation Detection and Scintillator Technologies (6 papers)
- Journals
- IEEE AccessNuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated EquipmentIEEE Transactions on Nuclear Science
- Partner nations
- ChinaUnited States
In The Last Decade
Quan Gan
24 papers receiving 392 citations
Peers
Comparison fields: 5 of 78
- Artificial Intelligence 214
- Computer Vision and Pattern Recognition 104
- Materials Chemistry 61
- Aerospace Engineering 58
- Radiation 54
Countries citing papers authored by Quan Gan
This map shows the geographic impact of Quan Gan'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 Quan Gan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quan Gan more than expected).
Fields of papers citing papers by Quan Gan
This network shows the impact of papers produced by Quan Gan. 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 Quan Gan. The network helps show where Quan Gan may publish in the future.
Co-authorship network of co-authors of Quan Gan
This figure shows the co-authorship network connecting the top 25 collaborators of Quan Gan. A scholar is included among the top collaborators of Quan Gan 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 Quan Gan. Quan Gan 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 | 1 | |
| 3 | 4 | |
| 4 | 6 | |
| 5 | 17 | |
| 6 | 3 | |
| 7 | 10 | |
| 8 | 4 | |
| 9 | 3 | |
| 10 | 12 | |
| 11 | 9 | |
| 12 | 5 | |
| 13 | 3 | |
| 14 | Deep Graph Library: Towards Efficient and Scalable Deep Learning on Graphs | 260 |
| 15 | 12 | |
| 16 | SegTree Transformer: Iterative refinement of hierarchical features | 1 |
| 17 | 8 | |
| 18 | 10 | |
| 19 | 1 | |
| 20 | 8 |
About Quan Gan
Quan Gan is a scholar working on Radiation, Acoustics and Ultrasonics and Aerospace Engineering, having authored 25 papers that have together received 404 indexed citations. Recurring topics across this work include Nuclear reactor physics and engineering (12 papers), Nuclear Physics and Applications (12 papers) and Radiation Detection and Scintillator Technologies (6 papers). The work is most often cited by research in Computational Mathematics (5 citations), Artificial Intelligence (214 citations) and Radiation (54 citations). Quan Gan has collaborated with scholars based in China and United States. Frequent co-authors include Zheng Zhang, Minjie Wang, Da Zheng, Qipeng Guo, Zihao Ye, Jinyang Li, Yu Gai, Chao Ma, Lingfan Yu and Jinjing Zhou. Their work appears in journals such as IEEE Access, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment and IEEE Transactions on Nuclear Science.
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.