Kaiyu Wan

716 citations
46 papers · 331 · h-index 11

Impact in

Papers in

Kaiyu Wan

44 papers receiving 308 citations

Peers

Kaiyu Wan
Comparison fields: 5 of 59
  • Computer Networks and Communications 138
  • Information Systems 106
  • Hardware and Architecture 23
  • Software 12
  • Computer Science Applications 17
Replace Hyun Jung La with:
Hyun Jung La South Korea
Ichiro Satoh Japan
Daniel Pakkala Finland
Markus Aleksy Germany
Aitor Urbieta Spain
Panagiotis Gouvas Greece
Krešimir Fertalj Croatia
Thorsten Kramp Germany
Jörg Heuer Germany
Dimitrios Papamartzivanos Greece
Kaiyu Wan relative to Hyun Jung La South Korea Hyun Jung La's profile →
Citations per field
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Citations per year

Countries citing papers authored by Kaiyu Wan

Since Specialization
Citations

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

Fields of papers citing papers by Kaiyu Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 23 scholars most cited alongside Kaiyu Wan, 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 Kaiyu Wan Line = papers co-authored together Kaiyu Wan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201828
2 201427
3
Specification, Analyzing Challenges and Approaches for Cyber-Physical Systems (CPS)
201026
4 201020
5 201219
6 201316
7 201415
8 201114
9
Using Web 2.0 tools to enhance learning in higher education: a case study in technological education
201212
10 201312
11 201311
12 201810
13 201610
14 20159
15
Investigation on Composition Mechanisms for Cyber Physical Systems
20158
16 20178
17 20127
18 20107
19 20177
20 20137

About Kaiyu Wan

Kaiyu Wan is a scholar working on Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering, having authored 46 papers that have together received 331 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (12 papers), IoT and Edge/Fog Computing (11 papers), Service-Oriented Architecture and Web Services (9 papers), Distributed systems and fault tolerance (7 papers), Advanced Software Engineering Methodologies (6 papers), Real-Time Systems Scheduling (5 papers), Embedded Systems Design Techniques (5 papers) and Smart Grid Security and Resilience (4 papers). The work is most often cited by research in Computer Networks and Communications (138 citations), Information Systems (106 citations), Hardware and Architecture (23 citations), Software (12 citations) and Computer Science Applications (17 citations). Kaiyu Wan has collaborated with scholars based in China, Canada and Lithuania. Frequent co-authors include Vangalur Alagar, Ka Lok Man, Tomas Krilavičius, D. Hughes, Chi‐Un Lei, Danny Hughes, V. S. Alagar, Yong Yue, Sheung-Hung Poon and J. Morris Chang. Their work appears in journals such as Mobile Networks and Applications, Sensors, International Journal of Distributed Sensor Networks, Algorithms and SHILAP Revista de lepidopterología.

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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