Ying-Hsun Lai
- Electrical and Electronic Engineering top 10%
- Computer Networks and Communications top 5%
- Atomic and Molecular Physics, and Optics
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 5%
- Co-authors
- Chin‐Feng LaiH. A. HausHan‐Chieh ChaoShih-Yeh ChenYu-Sheng SuYueh‐Min HuangYao‐Chung ChangYu‐Shan Lin
- Topics
- IoT and Edge/Fog Computing (10 papers)Smart Grid Energy Management (8 papers)IoT-based Smart Home Systems (8 papers)
- Cited by
- Computer Science ApplicationsComputer Networks and CommunicationsComputer Vision and Pattern Recognition
- Partner nations
- TaiwanChinaUnited States
In The Last Decade
Ying-Hsun Lai
48 papers receiving 856 citations
Peers
Comparison fields: 5 of 105
- Electrical and Electronic Engineering 340
- Computer Networks and Communications 173
- Atomic and Molecular Physics, and Optics 143
- Computer Vision and Pattern Recognition 140
- Information Systems 132
Countries citing papers authored by Ying-Hsun Lai
This map shows the geographic impact of Ying-Hsun Lai'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 Ying-Hsun Lai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying-Hsun Lai more than expected).
Fields of papers citing papers by Ying-Hsun Lai
This network shows the impact of papers produced by Ying-Hsun Lai. 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 Ying-Hsun Lai. The network helps show where Ying-Hsun Lai may publish in the future.
Co-authorship network of co-authors of Ying-Hsun Lai
This figure shows the co-authorship network connecting the top 25 collaborators of Ying-Hsun Lai. A scholar is included among the top collaborators of Ying-Hsun Lai 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 Ying-Hsun Lai. Ying-Hsun Lai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 4 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 5 | |
| 8 | 12 | |
| 9 | 26 | |
| 10 | 1 | |
| 11 | 12 | |
| 12 | 23 | |
| 13 | 23 | |
| 14 | 3 | |
| 15 | 13 | |
| 16 | 5 | |
| 17 | 9 | |
| 18 | 47 | |
| 19 | 16 | |
| 20 | 83 |
About Ying-Hsun Lai
Ying-Hsun Lai is a scholar working on Computer Science Applications, Human-Computer Interaction and Computer Vision and Pattern Recognition, having authored 50 papers that have together received 897 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (10 papers), Smart Grid Energy Management (8 papers) and IoT-based Smart Home Systems (8 papers). The work is most often cited by research in Computer Science Applications (73 citations), Computer Networks and Communications (173 citations) and Computer Vision and Pattern Recognition (140 citations). Ying-Hsun Lai has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Chin‐Feng Lai, H. A. Haus, Han‐Chieh Chao, Shih-Yeh Chen, Yu-Sheng Su, Yueh‐Min Huang, Shih-Yeh Chen, Yao‐Chung Chang, Yu‐Shan Lin and Chia‐Wei Tsai. Their work appears in journals such as Computers in Human Behavior, IEEE Access and Information Sciences.
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.