Jiaming Tang
Impact in
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- Catalysts for Methane Reforming
- Catalysis and Oxidation Reactions
Papers in
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- Face and Expression Recognition 2
- Advanced Neural Network Applications 1
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- Catalysts for Methane Reforming 4
- Catalysis and Oxidation Reactions 3
- Co-authors
- Guangxuan Xiao (1 shared paper)Song Han (1 shared paper)Haotian Tang (1 shared paper)Ji Lin (1 shared paper)Junguang Meng (4 shared papers)Changsheng Bu (4 shared papers)Guilin Piao (3 shared papers)Xinye Wang (4 shared papers)
- Journals
- Fuel (2 papers)Displays (1 paper)International Journal of Hydrogen Energy (1 paper)Systems Science & Control Engineering (1 paper)RSC Advances (1 paper)
- Partner nations
- ChinaUnited StatesJapan
In The Last Decade
Jiaming Tang
11 papers receiving 146 citations
Jiaming Tang's Hit Papers
Peers
Comparison fields: 5 of 47
- Catalysis 26
- Nuclear Energy and Engineering 1
- Computational Mathematics 1
- Computer Vision and Pattern Recognition 31
- Artificial Intelligence 38
Countries citing papers authored by Jiaming Tang
This map shows the geographic impact of Jiaming Tang'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 Jiaming Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiaming Tang more than expected).
Fields of papers citing papers by Jiaming Tang
This network shows the impact of papers produced by Jiaming Tang. 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 Jiaming Tang. The network helps show where Jiaming Tang may publish in the future.
Co-authors
The 25 scholars most cited alongside Jiaming Tang, 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 | AWQ: Activation-aware Weight Quantization for On-Device LLM Compression and Acceleration Hit paper breakdown → | 2025 | 77 |
| 2 | 2023 | 15 | |
| 3 | 2023 | 14 | |
| 4 | 2022 | 13 | |
| 5 | 2022 | 13 | |
| 6 | 2024 | 4 | |
| 7 | 2024 | 4 | |
| 8 | 2025 | 3 | |
| 9 | 2025 | 3 | |
| 10 | 2024 | 2 | |
| 11 | 2021 | 1 |
About Jiaming Tang
Jiaming Tang is a scholar working on Computer Vision and Pattern Recognition, Catalysis, Materials Chemistry, Aerospace Engineering and Mechanical Engineering, having authored 11 papers that have together received 149 indexed citations. Recurring topics across this work include Catalytic Processes in Materials Science (4 papers), Catalysts for Methane Reforming (4 papers), Catalysis and Oxidation Reactions (3 papers), Face and Expression Recognition (2 papers), Catalysis and Hydrodesulfurization Studies (2 papers), Advanced Antenna and Metasurface Technologies (1 paper), Digital Media and Visual Art (1 paper) and Advanced Neural Network Applications (1 paper). The work is most often cited by research in Catalysis (26 citations), Nuclear Energy and Engineering (1 citation), Computational Mathematics (1 citation), Computer Vision and Pattern Recognition (31 citations) and Artificial Intelligence (38 citations). Jiaming Tang has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Guangxuan Xiao, Song Han, Haotian Tang, Ji Lin, Junguang Meng, Changsheng Bu, Guilin Piao, Xinye Wang, Jubing Zhang and Chunyu Lin. Their work appears in journals such as Fuel, Displays, International Journal of Hydrogen Energy, Systems Science & Control Engineering and RSC Advances.
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.