Weilan Lin
Impact in
-
- Software System Performance and Reliability
- IoT and Edge/Fog Computing
-
- Digital Transformation in Industry
Papers in
-
- Software System Performance and Reliability 5
- Energy Efficient Wireless Sensor Networks 1
-
- Railway Systems and Energy Efficiency 1
- Digital Transformation in Industry 1
- Co-authors
- Meng Ma (9 shared papers)Ping Wang (9 shared papers)Pengfei Chen (1 shared paper)Jingmin Xu (1 shared paper)Yuchen Zhou (2 shared papers)Yangxin Lin (1 shared paper)Jingbin Zhang (2 shared papers)Ping Wang (1 shared paper)
In The Last Decade
Weilan Lin
10 papers receiving 294 citations
Peers
Comparison fields: 5 of 36
- Computer Networks and Communications 219
- Industrial and Manufacturing Engineering 19
- Information Systems 24
- Artificial Intelligence 25
- Control and Systems Engineering 17
Countries citing papers authored by Weilan Lin
This map shows the geographic impact of Weilan Lin'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 Weilan Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weilan Lin more than expected).
Fields of papers citing papers by Weilan Lin
This network shows the impact of papers produced by Weilan Lin. 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 Weilan Lin. The network helps show where Weilan Lin may publish in the future.
Co-authors
The 11 scholars most cited alongside Weilan Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 111 | |
| 2 | 2019 | 39 | |
| 3 | 2017 | 33 | |
| 4 | 2017 | 30 | |
| 5 | 2021 | 30 | |
| 6 | 2020 | 26 | |
| 7 | 2018 | 22 | |
| 8 | 2017 | 4 | |
| 9 | 2017 | 1 | |
| 10 | 2018 | 1 | |
| 11 | 2024 | 1 | |
| 12 | 2017 | 0 | |
| 13 | 2025 | 0 | |
| 14 | 2026 | 0 | |
| 15 | 2026 | 0 |
About Weilan Lin
Weilan Lin is a scholar working on Computer Networks and Communications, Industrial and Manufacturing Engineering, Oncology, Computer Graphics and Computer-Aided Design and Information Systems, having authored 15 papers that have together received 298 indexed citations. Recurring topics across this work include Software System Performance and Reliability (5 papers), Cognitive Computing and Networks (2 papers), Smart Grid Energy Management (2 papers), Railway Systems and Energy Efficiency (1 paper), Digital Transformation in Industry (1 paper), Cancer survivorship and care (1 paper), Musculoskeletal pain and rehabilitation (1 paper) and Energy Efficient Wireless Sensor Networks (1 paper). The work is most often cited by research in Computer Networks and Communications (219 citations), Industrial and Manufacturing Engineering (19 citations), Information Systems (24 citations), Artificial Intelligence (25 citations) and Control and Systems Engineering (17 citations). Weilan Lin has collaborated with scholars based in China and Australia. Frequent co-authors include Meng Ma, Ping Wang, Pengfei Chen, Jingmin Xu, Yuchen Zhou, Yuchen Zhou, Yangxin Lin, Jingbin Zhang, Ping Wang and Shun Chen. Their work appears in journals such as Frontiers in Oncology, IEEE Transactions on Industrial Informatics, Medicine, 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.