Dejun Mu

604 citations
48 papers · 463 · h-index 10

Impact in

  • Software top 10%
    • Software Reliability and Analysis Research
    • Recommender Systems and Techniques
    • Software Engineering Research

Papers in

    • Software Engineering Research 7
    • Recommender Systems and Techniques 5
    • Web Data Mining and Analysis 3
    • Text and Document Classification Technologies 6
    • Cryptographic Implementations and Security 5

Dejun Mu

41 papers receiving 440 citations

Peers

Dejun Mu
Comparison fields: 5 of 68
  • Software 39
  • Information Systems 207
  • Artificial Intelligence 248
  • Hardware and Architecture 37
  • Signal Processing 58
Replace Qinkai Zheng with:
Qinkai Zheng China
Jingyu Zhang China
He Yan United States
Sanjay Kumar India
Grzegorz Borowik Poland
Moez Mnif Germany
Eduardo Sany Laber Brazil
Weizhong Qiang China
Liwei Kuang China
Dejun Mu relative to Qinkai Zheng China Qinkai Zheng's profile →
Citations per field
00.5×2×3×3.6×
Qinkai Zheng · 1×
Citations per year

Countries citing papers authored by Dejun Mu

Since Specialization
Citations

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

Fields of papers citing papers by Dejun Mu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dejun Mu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Dejun Mu Line = papers co-authored together Dejun Mu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202186
2 201875
3 201739
4 202336
5 201732
6 201930
7 201816
8 202114
9 201911
10 201911
11 20079
12 20178
13 20208
14 20177
15 20206
16 20126
17 20116
18 20195
19 20185
20 20135

About Dejun Mu

Dejun Mu is a scholar working on Information Systems, Artificial Intelligence, Signal Processing, Hardware and Architecture and Software, having authored 48 papers that have together received 463 indexed citations. Recurring topics across this work include Software Engineering Research (7 papers), Physical Unclonable Functions (PUFs) and Hardware Security (6 papers), Text and Document Classification Technologies (6 papers), Advanced Malware Detection Techniques (6 papers), Cryptographic Implementations and Security (5 papers), Recommender Systems and Techniques (5 papers), Software Testing and Debugging Techniques (4 papers) and Web Data Mining and Analysis (3 papers). The work is most often cited by research in Software (39 citations), Information Systems (207 citations), Artificial Intelligence (248 citations), Hardware and Architecture (37 citations) and Signal Processing (58 citations). Dejun Mu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Xiaoyan Cai, Lantian Guo, Xiaoxue Wu, Xiang Chen, Libin Yang, Fei Hao, Wei Zheng, Tingting Yu, Yu Mei Zhao and Hang Dai. Their work appears in journals such as IEEE Access, IEEE Internet of Things Journal, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Tsinghua Science & Technology and Journal of Intelligent & Fuzzy Systems.

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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