Yichen Chen
- Computer Vision and Pattern Recognition top 5%
- Materials Chemistry
- Biomedical Engineering
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Co-authors
- Vishal M. PatelRama ChellappaP. Jonathon PhillipsHong LiuQing HaoSumit ShekharYung‐Chin DingC. S. Sastry
- Topics
- Sparse and Compressive Sensing Techniques (5 papers)Concrete and Cement Materials Research (5 papers)Advanced Image and Video Retrieval Techniques (5 papers)
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Yichen Chen
43 papers receiving 500 citations
Peers
Comparison fields: 5 of 86
- Computer Vision and Pattern Recognition 161
- Materials Chemistry 120
- Biomedical Engineering 117
- Artificial Intelligence 95
- Electrical and Electronic Engineering 83
Countries citing papers authored by Yichen Chen
This map shows the geographic impact of Yichen Chen'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 Yichen Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yichen Chen more than expected).
Fields of papers citing papers by Yichen Chen
This network shows the impact of papers produced by Yichen Chen. 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 Yichen Chen. The network helps show where Yichen Chen may publish in the future.
Co-authorship network of co-authors of Yichen Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Yichen Chen. A scholar is included among the top collaborators of Yichen Chen 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 Yichen Chen. Yichen Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 3 | |
| 3 | 2 | |
| 4 | 19 | |
| 5 | 34 | |
| 6 | 11 | |
| 7 | 30 | |
| 8 | 5 | |
| 9 | 2 | |
| 10 | 3 | |
| 11 | 29 | |
| 12 | 2 | |
| 13 | 9 | |
| 14 | Approximation Hardness for A Class of Sparse Optimization Problems | 9 |
| 15 | Strong NP-hardness for sparse optimization with concave penalty functions | 4 |
| 16 | 1 | |
| 17 | 3 | |
| 18 | 22 | |
| 19 | 20 | |
| 20 | 1 |
About Yichen Chen
Yichen Chen is a scholar working on General Engineering, Computer Vision and Pattern Recognition and Media Technology, having authored 43 papers that have together received 514 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (5 papers), Concrete and Cement Materials Research (5 papers) and Advanced Image and Video Retrieval Techniques (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (161 citations), Signal Processing (45 citations) and Artificial Intelligence (95 citations). Yichen Chen has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Vishal M. Patel, Rama Chellappa, P. Jonathon Phillips, Hong Liu, Qing Hao, Sumit Shekhar, Yung‐Chin Ding, C. S. Sastry, Chao Zhao and Dong Wang. Their work appears in journals such as Nature Communications, ACS Nano and Chemical Engineering Journal.
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.