Yu‐Hsin Chen
- Hardware and Architecture top 0.5%
-
- Advanced Neural Network Applications 13
- Computational Mathematics top 2%
- Artificial Intelligence top 0.5%
-
- Advanced Memory and Neural Computing 9
- Photonic and Optical Devices 6
-
- Laser-Matter Interactions and Applications 33
- Advanced Fiber Laser Technologies 13
- Spectroscopy and Quantum Chemical Studies 6
-
- Laser-Plasma Interactions and Diagnostics 20
-
- Laser-induced spectroscopy and plasma 16
- Partner nations
- United StatesTaiwanChina
In The Last Decade
Yu‐Hsin Chen
121 papers receiving 6.7k citations
Hit Papers
Peers
Comparison fields: 5 of 186
- Hardware and Architecture 861
- Computer Vision and Pattern Recognition 2.5k
- Computational Mathematics 72
- Artificial Intelligence 1.9k
- Electrical and Electronic Engineering 2.8k
Countries citing papers authored by Yu‐Hsin Chen
This map shows the geographic impact of Yu‐Hsin 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 Yu‐Hsin Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu‐Hsin Chen more than expected).
Fields of papers citing papers by Yu‐Hsin Chen
This network shows the impact of papers produced by Yu‐Hsin 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 Yu‐Hsin Chen. The network helps show where Yu‐Hsin Chen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yu‐Hsin Chen, 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 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 17 | |
| 4 | 2024 | 2 | |
| 5 | 2023 | 10 | |
| 6 | 2023 | 2 | |
| 7 | 2023 | 20 | |
| 8 | Multi-Scale High-Resolution Vision Transformer for Semantic Segmentationbreakdown → | 2022 | 167 |
| 9 | 2021 | 1 | |
| 10 | 2020 | 16 | |
| 11 | 2017 | 129 | |
| 12 | Eyerissbreakdown → | 2016 | 868 |
| 13 | 2016 | 31 | |
| 14 | 2016 | 32 | |
| 15 | 2015 | 47 | |
| 16 | 2015 | 24 | |
| 17 | 2013 | 9 | |
| 18 | 2010 | 113 | |
| 19 | 2009 | 20 | |
| 20 | 1995 | 3 |
About Yu‐Hsin Chen
Yu‐Hsin Chen is a scholar working on Computational Mathematics, Nuclear and High Energy Physics, Atomic and Molecular Physics, and Optics, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 128 papers that have together received 6.9k indexed citations. Recurring topics across this work include Laser-Matter Interactions and Applications (33 papers), Laser-Plasma Interactions and Diagnostics (20 papers), Laser-induced spectroscopy and plasma (16 papers), Advanced Neural Network Applications (13 papers), Advanced Fiber Laser Technologies (13 papers), Advanced Memory and Neural Computing (9 papers), Spectroscopy and Quantum Chemical Studies (6 papers) and Photonic and Optical Devices (6 papers). The work is most often cited by research in Hardware and Architecture (861 citations), Computer Vision and Pattern Recognition (2.5k citations), Computational Mathematics (72 citations), Artificial Intelligence (1.9k citations) and Electrical and Electronic Engineering (2.8k citations). Yu‐Hsin Chen has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Joel Emer, Vivienne Sze, Tien-Ju Yang, H. M. Milchberg, S. Varma, Wen‐Jing Yan, Xiaolan Fu, Jing Liang, Qi Wu and Thomas M. Antonsen. Their work appears in journals such as Physics of Plasmas, Physical Review Letters, Optics Express, Industrial & Engineering Chemistry Research and IEEE Micro.
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.