Xipeng Shen

7.7k total citations · 1 hit paper
213 papers, 5.3k citations indexed

About

Xipeng Shen is a scholar working on Hardware and Architecture, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Xipeng Shen has authored 213 papers receiving a total of 5.3k indexed citations (citations by other indexed papers that have themselves been cited), including 131 papers in Hardware and Architecture, 115 papers in Computer Networks and Communications and 83 papers in Artificial Intelligence. Recurrent topics in Xipeng Shen's work include Parallel Computing and Optimization Techniques (127 papers), Advanced Data Storage Technologies (64 papers) and Distributed and Parallel Computing Systems (27 papers). Xipeng Shen is often cited by papers focused on Parallel Computing and Optimization Techniques (127 papers), Advanced Data Storage Technologies (64 papers) and Distributed and Parallel Computing Systems (27 papers). Xipeng Shen collaborates with scholars based in United States, China and Canada. Xipeng Shen's co-authors include Matthew Boutell, Jiebo Luo, Christopher M. Brown, Chen Ding, Yunlian Jiang, Yutao Zhong, Eddy Z. Zhang, Guoyang Chen, Bo Wu and Jidong Zhai and has published in prestigious journals such as SHILAP Revista de lepidopterología, Advanced Functional Materials and Communications of the ACM.

In The Last Decade

Xipeng Shen

204 papers receiving 5.1k citations

Hit Papers

Learning multi-label scene classification 2004 2026 2011 2018 2004 500 1000 1.5k

Peers

Xipeng Shen
Comparison fields: 5 of 124
  • Computer Networks and Communications 2.3k
  • Hardware and Architecture 2.3k
  • Artificial Intelligence 2.3k
  • Information Systems 1.5k
  • Computer Vision and Pattern Recognition 1.3k
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Citations per field, relative to Xipeng Shen
Xipeng Shen · 1×
Citations per year, relative to Xipeng Shen
Xipeng Shen · 1×

Countries citing papers authored by Xipeng Shen

Since Specialization
Citations

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

Fields of papers citing papers by Xipeng Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xipeng Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Xipeng Shen. A scholar is included among the top collaborators of Xipeng Shen 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 Xipeng Shen. Xipeng Shen 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
# Work Indexed citations
1 0
2 1
3 0
4 3
5 1
6 1
7 4
8 8
9 1
10 3
11 14
12
FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks.
2
13 20
14 1
15
Yinyang K-Means: A Drop-In Replacement of the Classic K-Means with Consistent Speedup
59
16
Simple Profile Rectifications Go A Long Way —Statistically Exploring and Alleviating the Effects of Sampling Errors for Program Optimizations
3
17 48
18 14
19 1
20 4

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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