Shih-Yuan Yu
- Electrical and Electronic Engineering
- Artificial Intelligence top 10%
- Industrial and Manufacturing Engineering top 5%
- Hardware and Architecture top 5%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Mohammad Abdullah Al FaruquePramod P. KhargonekarDeepan MuthirayanArnav Vaibhav MalawadeRozhin YasaeiChun‐Ching HsiaoJane Yung-jen HsuKwei-Jay Lin
- Topics
- Gas Sensing Nanomaterials and Sensors (3 papers)ZnO doping and properties (3 papers)Physical Unclonable Functions (PUFs) and Hardware Security (3 papers)
- Partner nations
- United StatesTaiwan
In The Last Decade
Shih-Yuan Yu
19 papers receiving 446 citations
Peers
Comparison fields: 5 of 63
- Electrical and Electronic Engineering 133
- Artificial Intelligence 105
- Industrial and Manufacturing Engineering 94
- Hardware and Architecture 93
- Computer Vision and Pattern Recognition 74
Countries citing papers authored by Shih-Yuan Yu
This map shows the geographic impact of Shih-Yuan Yu'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 Shih-Yuan Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shih-Yuan Yu more than expected).
Fields of papers citing papers by Shih-Yuan Yu
This network shows the impact of papers produced by Shih-Yuan Yu. 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 Shih-Yuan Yu. The network helps show where Shih-Yuan Yu may publish in the future.
Co-authorship network of co-authors of Shih-Yuan Yu
This figure shows the co-authorship network connecting the top 25 collaborators of Shih-Yuan Yu. A scholar is included among the top collaborators of Shih-Yuan Yu 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 Shih-Yuan Yu. Shih-Yuan Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 5 | |
| 4 | 23 | |
| 5 | 33 | |
| 6 | 3 | |
| 7 | 54 | |
| 8 | 44 | |
| 9 | 54 | |
| 10 | 67 | |
| 11 | 31 | |
| 12 | 31 | |
| 13 | 42 | |
| 14 | 11 | |
| 15 | 6 | |
| 16 | Leveraging Persuasive Feedback Mechanism for Problem Solving. | 1 |
| 17 | 34 | |
| 18 | 7 | |
| 19 | 8 | |
| 20 | 1 |
About Shih-Yuan Yu
Shih-Yuan Yu is a scholar working on Hardware and Architecture, Industrial and Manufacturing Engineering and Automotive Engineering, having authored 20 papers that have together received 462 indexed citations. Recurring topics across this work include Gas Sensing Nanomaterials and Sensors (3 papers), ZnO doping and properties (3 papers) and Physical Unclonable Functions (PUFs) and Hardware Security (3 papers). The work is most often cited by research in Hardware and Architecture (93 citations), Industrial and Manufacturing Engineering (94 citations) and Automotive Engineering (67 citations). Shih-Yuan Yu has collaborated with scholars based in United States and Taiwan. Frequent co-authors include Mohammad Abdullah Al Faruque, Pramod P. Khargonekar, Deepan Muthirayan, Arnav Vaibhav Malawade, Rozhin Yasaei, Chun‐Ching Hsiao, Jane Yung-jen Hsu, Kwei-Jay Lin, Liming Chen and Sujit Rokka Chhetri. Their work appears in journals such as IEEE Access, Sensors and IEEE Transactions on Intelligent Transportation Systems.
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.