De-yu Shen
Impact in
- Hardware and Architecture top 5%
- Parallel Computing and Optimization Techniques
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- Advanced Data Storage Technologies
Papers in
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- Parallel Computing and Optimization Techniques 5
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- Advanced Data Storage Technologies 3
- Distributed systems and fault tolerance 2
- Co-authors
- Chia-Lin Yang (5 shared papers)Ren-Shuo Liu (3 shared papers)Alpa M. Nick (1 shared paper)Edna Mora (1 shared paper)Rebecca L. Stone (1 shared paper)Lingegowda S. Mangala (1 shared paper)Mian M.K. Shahzad (1 shared paper)Ju‐Won Roh (1 shared paper)
- Journals
- Clinical Cancer Research (1 paper)Foods (1 paper)ACM SIGPLAN Notices (1 paper)International Journal of Molecular Sciences (1 paper)Pharmaceutical Research (1 paper)
- Partner nations
- TaiwanChinaUnited States
In The Last Decade
De-yu Shen
8 papers receiving 371 citations
Peers
Comparison fields: 5 of 51
- Hardware and Architecture 129
- Computer Networks and Communications 126
- Biomaterials 68
- Pharmaceutical Science 23
- Cancer Research 35
Countries citing papers authored by De-yu Shen
This map shows the geographic impact of De-yu Shen'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 De-yu Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites De-yu Shen more than expected).
Fields of papers citing papers by De-yu Shen
This network shows the impact of papers produced by De-yu Shen. 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 De-yu Shen. The network helps show where De-yu Shen may publish in the future.
Co-authors
The 25 scholars most cited alongside De-yu Shen, 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 | 2010 | 203 | |
| 2 | 2014 | 86 | |
| 3 | 2012 | 49 | |
| 4 | 2014 | 10 | |
| 5 | 2022 | 9 | |
| 6 | 2014 | 8 | |
| 7 | 2008 | 7 | |
| 8 | 2015 | 5 | |
| 9 | 2025 | 0 |
About De-yu Shen
De-yu Shen is a scholar working on Hardware and Architecture, Computer Networks and Communications, Electrical and Electronic Engineering, Molecular Biology and Nutrition and Dietetics, having authored 9 papers that have together received 377 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (5 papers), Advanced Data Storage Technologies (3 papers), Low-power high-performance VLSI design (2 papers), Radiation Effects in Electronics (2 papers), Distributed systems and fault tolerance (2 papers), Advanced Memory and Neural Computing (1 paper), MXene and MAX Phase Materials (1 paper) and 2D Materials and Applications (1 paper). The work is most often cited by research in Hardware and Architecture (129 citations), Computer Networks and Communications (126 citations), Biomaterials (68 citations), Pharmaceutical Science (23 citations) and Cancer Research (35 citations). De-yu Shen has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Chia-Lin Yang, Ren-Shuo Liu, Alpa M. Nick, Edna Mora, Rebecca L. Stone, Lingegowda S. Mangala, Mian M.K. Shahzad, Ju‐Won Roh, Anil K. Sood and Gabriel Lopez‐Berestein. Their work appears in journals such as Clinical Cancer Research, Foods, ACM SIGPLAN Notices, International Journal of Molecular Sciences and Pharmaceutical Research.
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.