Chengyong Wu

3.4k citations
52 papers · 2.5k indexed · 2 hit papers · h-index 18
Topics
Parallel Computing and Optimization Techniques (28 papers)Advanced Data Storage Technologies (12 papers)Cloud Computing and Resource Management (11 papers)
Partner nations
ChinaFranceBelgium

In The Last Decade

Chengyong Wu

51 papers receiving 2.4k citations

Hit Papers

DianNao201420262018202220142022250500750

Peers

Chengyong Wu
Comparison fields: 5 of 115
  • Electrical and Electronic Engineering 1.1k
  • Computer Vision and Pattern Recognition 924
  • Hardware and Architecture 765
  • Artificial Intelligence 602
  • Computer Networks and Communications 535
Replace Daehyun Kim with:
Daehyun Kim United States
Tal Ben‐Nun Switzerland
Yunsup Lee United States
Lin Gan China
Yibo Lin China
Darren J. Kerbyson United States
Manjunath V. Joshi India
Ronak Singhal United States
Jiajun Li China
Tarek El‐Ghazawi United States
Chengyong Wu relative to Daehyun Kim United States Daehyun Kim's profile →
Citations per field
00.5×4.5×
Daehyun Kim · 1×
Citations per year

Countries citing papers authored by Chengyong Wu

Since Specialization
Citations

This map shows the geographic impact of Chengyong Wu'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 Chengyong Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chengyong Wu more than expected).

Fields of papers citing papers by Chengyong Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chengyong Wu. 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 Chengyong Wu. The network helps show where Chengyong Wu may publish in the future.

Co-authorship network of co-authors of Chengyong Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Chengyong Wu. A scholar is included among the top collaborators of Chengyong Wu 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 Chengyong Wu. Chengyong Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 5
2 6
3 20
4
A paper-based assay for the colorimetric detection of SARS-CoV-2 variants at single-nucleotide resolutionbreakdown →
152
5 55
6 6
7 50
8 13
9 1
10 13
11 20
12 213
13 5
14 94
15 14
16
Transforming GCC into a research-friendly environment: plugins for optimization tuning and reordering, function cloning and program instrumentation
5
17 49
18 1
19 1
20 3

About Chengyong Wu

Chengyong Wu is a scholar working on Hardware and Architecture, Computer Networks and Communications and Information Systems, having authored 52 papers that have together received 2.5k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (28 papers), Advanced Data Storage Technologies (12 papers) and Cloud Computing and Resource Management (11 papers). The work is most often cited by research in Hardware and Architecture (765 citations), Computer Vision and Pattern Recognition (924 citations) and Computational Mathematics (23 citations). Chengyong Wu has collaborated with scholars based in China, France and Belgium. Frequent co-authors include Olivier Temam, Yunji Chen, Zidong Du, Tianshi Chen, Ninghui Sun, Jia Wang, Ninghui Sun, Lei Liu, Mingyu Chen and Zehan Cui. Their work appears in journals such as Nature Communications, Sustainability and European Journal of Medicinal Chemistry.

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.

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