Yuechen Wang
Impact in
- Human-Computer Interaction top 5%
- Hand Gesture Recognition Systems
- Aging top 10%
Papers in
-
- Ubiquitin and proteasome pathways 5
- Protein Degradation and Inhibitors 5
- Mitochondrial Function and Pathology 4
-
- Graphene research and applications 5
- 2D Materials and Applications 3
- Co-authors
- Houqiang Li (2 shared papers)Wengang Zhou (2 shared papers)Luzhao Sun (5 shared papers)Zhongfan Liu (5 shared papers)Yanglizhi Li (4 shared papers)Hailin Peng (4 shared papers)Weichao Zhao (1 shared paper)Hezhen Hu (1 shared paper)
- Journals
- ACS Nano (2 papers)Journal of the American Chemical Society (2 papers)Frontiers in Genetics (2 papers)ACS Chemical Biology (2 papers)Gene (1 paper)
- Partner nations
- ChinaJapanUnited States
In The Last Decade
Yuechen Wang
40 papers receiving 805 citations
Peers
Comparison fields: 5 of 119
- Human-Computer Interaction 68
- Aging 19
- Materials Chemistry 235
- Computer Vision and Pattern Recognition 94
- Rehabilitation 27
Countries citing papers authored by Yuechen Wang
This map shows the geographic impact of Yuechen 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 Yuechen Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuechen Wang more than expected).
Fields of papers citing papers by Yuechen Wang
This network shows the impact of papers produced by Yuechen 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 Yuechen Wang. The network helps show where Yuechen Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Yuechen 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
Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 82 | |
| 2 | 2021 | 78 | |
| 3 | 2021 | 72 | |
| 4 | 2024 | 64 | |
| 5 | 2023 | 52 | |
| 6 | 2024 | 50 | |
| 7 | 2023 | 48 | |
| 8 | 2021 | 37 | |
| 9 | 2020 | 33 | |
| 10 | 2021 | 29 | |
| 11 | 2019 | 27 | |
| 12 | 2013 | 21 | |
| 13 | 2020 | 20 | |
| 14 | 2016 | 18 | |
| 15 | 2020 | 18 | |
| 16 | 2022 | 17 | |
| 17 | 2019 | 17 | |
| 18 | 2019 | 15 | |
| 19 | 2024 | 13 | |
| 20 | 2019 | 13 |
About Yuechen Wang
Yuechen Wang is a scholar working on Molecular Biology, Materials Chemistry, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Atomic and Molecular Physics, and Optics, having authored 45 papers that have together received 829 indexed citations. Recurring topics across this work include Ubiquitin and proteasome pathways (5 papers), Protein Degradation and Inhibitors (5 papers), Graphene research and applications (5 papers), Genetics, Aging, and Longevity in Model Organisms (4 papers), Mitochondrial Function and Pathology (4 papers), 2D Materials and Applications (3 papers), Advancements in Battery Materials (3 papers) and Peptidase Inhibition and Analysis (3 papers). The work is most often cited by research in Human-Computer Interaction (68 citations), Aging (19 citations), Materials Chemistry (235 citations), Computer Vision and Pattern Recognition (94 citations) and Rehabilitation (27 citations). Yuechen Wang has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Houqiang Li, Wengang Zhou, Luzhao Sun, Zhongfan Liu, Yanglizhi Li, Hailin Peng, Weichao Zhao, Hezhen Hu, Haiyang Liu and Weiyu Chen. Their work appears in journals such as ACS Nano, Journal of the American Chemical Society, Frontiers in Genetics, ACS Chemical Biology and Gene.
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.