Carl Yang
Impact in
- Hardware and Architecture top 5%
- Parallel Computing and Optimization Techniques
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- Graph Theory and Algorithms
Papers in
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- Graph Theory and Algorithms 10
- Handwritten Text Recognition Techniques 1
- Video Analysis and Summarization 1
- Image Retrieval and Classification Techniques 1
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- Advanced Graph Neural Networks 6
- Co-authors
- John D. Owens (7 shared papers)Aydın Buluç (6 shared papers)Yangzihao Wang (4 shared papers)Yuduo Wu (3 shared papers)Yuechao Pan (3 shared papers)José E. Moreira (3 shared papers)Scott McMillan (3 shared papers)Tim Mattson (2 shared papers)
- Journals
- ACM Transactions on Mathematical Software (1 paper)eScholarship (California Digital Library) (6 papers)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Carl Yang
12 papers receiving 304 citations
Peers
Comparison fields: 5 of 30
- Hardware and Architecture 155
- Computer Vision and Pattern Recognition 220
- Computational Mathematics 5
- Computer Networks and Communications 131
- Artificial Intelligence 140
Countries citing papers authored by Carl Yang
This map shows the geographic impact of Carl Yang'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 Carl Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Carl Yang more than expected).
Fields of papers citing papers by Carl Yang
This network shows the impact of papers produced by Carl Yang. 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 Carl Yang. The network helps show where Carl Yang may publish in the future.
Co-authors
The 21 scholars most cited alongside Carl Yang, 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 | 2017 | 88 | |
| 2 | 2022 | 40 | |
| 3 | 2017 | 38 | |
| 4 | 2017 | 34 | |
| 5 | 2015 | 22 | |
| 6 | 2019 | 20 | |
| 7 | 2018 | 20 | |
| 8 | 2019 | 17 | |
| 9 | 2017 | 16 | |
| 10 | 2015 | 15 | |
| 11 | 2023 | 2 | |
| 12 | 2022 | 2 | |
| 13 | 2025 | 0 |
About Carl Yang
Carl Yang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Hardware and Architecture, Information Systems and Computational Theory and Mathematics, having authored 13 papers that have together received 314 indexed citations. Recurring topics across this work include Graph Theory and Algorithms (10 papers), Advanced Graph Neural Networks (6 papers), Parallel Computing and Optimization Techniques (5 papers), Cloud Computing and Resource Management (2 papers), Complexity and Algorithms in Graphs (2 papers), Handwritten Text Recognition Techniques (1 paper), Video Analysis and Summarization (1 paper) and Image Retrieval and Classification Techniques (1 paper). The work is most often cited by research in Hardware and Architecture (155 citations), Computer Vision and Pattern Recognition (220 citations), Computational Mathematics (5 citations), Computer Networks and Communications (131 citations) and Artificial Intelligence (140 citations). Carl Yang has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include John D. Owens, Aydın Buluç, Yangzihao Wang, Yuduo Wu, Yuechao Pan, José E. Moreira, Scott McMillan, Tim Mattson, Leyuan Wang and Weitang Liu. Their work appears in journals such as ACM Transactions on Mathematical Software and eScholarship (California Digital Library).
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.