Dayong Ye

2.1k citations
75 papers · 1.3k · h-index 20

Impact in

Papers in

Dayong Ye

70 papers receiving 1.3k citations

Peers

Dayong Ye
Comparison fields: 5 of 90
  • Computer Networks and Communications 560
  • Artificial Intelligence 543
  • Information Systems 346
  • Computer Science Applications 74
  • Signal Processing 85
Replace Muneeb Ul Hassan with:
Muneeb Ul Hassan Australia
Dinesh Verma United States
Xiaoxian Yang China
Ole‐Christoffer Granmo Norway
Yan Jia China
Wajid Rafique China
Fuyuki Ishikawa Japan
Hejiao Huang China
Hongyang Yan China
Sajjan G. Shiva United States
Dayong Ye relative to Muneeb Ul Hassan Australia Muneeb Ul Hassan's profile →
Citations per field
00.5×2.9×
Muneeb Ul Hassan · 1×
Citations per year

Countries citing papers authored by Dayong Ye

Since Specialization
Citations

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

Fields of papers citing papers by Dayong Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dayong Ye, 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 Dayong Ye Line = papers co-authored together Dayong Ye links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 75 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016163
2 201799
3 201696
4 201172
5 202266
6 202163
7 201555
8 202253
9 201645
10 201344
11 201736
12 202231
13 202030
14 201929
15 202225
16 201723
17 202222
18 201621
19 202119
20 202019

About Dayong Ye

Dayong Ye is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Sociology and Political Science and Computer Science Applications, having authored 75 papers that have together received 1.3k indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (23 papers), Adversarial Robustness in Machine Learning (12 papers), Service-Oriented Architecture and Web Services (10 papers), Mobile Crowdsensing and Crowdsourcing (9 papers), Network Security and Intrusion Detection (9 papers), Peer-to-Peer Network Technologies (8 papers), Advanced Software Engineering Methodologies (7 papers) and Evolutionary Game Theory and Cooperation (6 papers). The work is most often cited by research in Computer Networks and Communications (560 citations), Artificial Intelligence (543 citations), Information Systems (346 citations), Computer Science Applications (74 citations) and Signal Processing (85 citations). Dayong Ye has collaborated with scholars based in Australia, Macao and China. Frequent co-authors include Minjie Zhang, Tianqing Zhu, Wanlei Zhou, Yan Kong, Danny Sutanto, Qiang He, Yun Yang, Yanchun Wang, Athanasios V. Vasilakos and Philip S. Yu. Their work appears in journals such as Knowledge-Based Systems, IEEE Internet of Things Journal, IEEE Transactions on Information Forensics and Security, IEEE Transactions on Dependable and Secure Computing and IEEE Transactions on Services Computing.

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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