Wujie Wen

479 citations
16 papers · 126 indexed · h-index 7
Topics
Adversarial Robustness in Machine Learning (6 papers)Privacy-Preserving Technologies in Data (5 papers)Cryptography and Data Security (4 papers)
Journals
The Journal of SupercomputingACM Transactions on Architecture and Code OptimizationProceedings of the 59th ACM/IEEE Design Automation Conference

In The Last Decade

Wujie Wen

15 papers receiving 123 citations

Peers

Wujie Wen
Comparison fields: 5 of 42
  • Electrical and Electronic Engineering 52
  • Artificial Intelligence 47
  • Computer Vision and Pattern Recognition 34
  • Hardware and Architecture 32
  • Computer Networks and Communications 22
Replace Hangrui Bi with:
Hangrui Bi China
Ioannis A. Papistas Belgium
Jaehoon Yu Japan
Vikash Kumar India
Joonsoo Kwon South Korea
Ben Smeets Sweden
Mingtao Zhan China
Juliane Krämer Germany
Greg Diamos China
Amir Gholami United States
Wujie Wen relative to Hangrui Bi China Hangrui Bi's profile →
Citations per field
00.5×
Hangrui Bi · 1×
Citations per year

Countries citing papers authored by Wujie Wen

Since Specialization
Citations

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

Fields of papers citing papers by Wujie Wen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wujie Wen

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

All Works

16 of 16 papers shown
#WorkIndexed citations
1 0
2 1
3 1
4 11
5 1
6 9
7 1
8 2
9 1
10 36
11 10
12 9
13 3
14 26
15 6
16 9

About Wujie Wen

Wujie Wen is a scholar working on Health Informatics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 16 papers that have together received 126 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (6 papers), Privacy-Preserving Technologies in Data (5 papers) and Cryptography and Data Security (4 papers). The work is most often cited by research in Hardware and Architecture (32 citations), Computer Vision and Pattern Recognition (34 citations) and Artificial Intelligence (47 citations). Wujie Wen has collaborated with scholars based in United States, Mexico and Australia. Frequent co-authors include Yiran Chen, Yaojun Zhang, Mengjie Mao, Caiwen Ding, Hongwu Peng, Qi Liu, Yanzhi Wang, Jinbo Bi, Yiyu Shi and Shiyang Chen. Their work appears in journals such as The Journal of Supercomputing, ACM Transactions on Architecture and Code Optimization and Proceedings of the 59th ACM/IEEE Design Automation Conference.

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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