Sinan Li

9 papers receiving 678 citations

Sinan Li's Hit Papers

The emerging graph neural networks for intelligent fault diagnostics and prognostics: A guideline and a benchmark study 2021 · 445 citations
4450+1+3Years since publication100200300400

Peers

Sinan Li
Comparison fields: 5 of 78
  • Control and Systems Engineering 458
  • Medical Laboratory Technology 13
  • Mechanics of Materials 138
  • Artificial Intelligence 178
  • Safety, Risk, Reliability and Quality 44
Replace Chaoying Yang with:
Chaoying Yang China
Xuefeng Chen China
Jichao Zhuang China
Daoming She China
Alexander E. Prosvirin South Korea
Chenyu Liu China
Tarek Berghout Algeria
Nader Fnaiech France
Jialin Li China
Huaiqian Bao China
Sinan Li relative to Chaoying Yang China Chaoying Yang's profile →
Citations per field
00.5×1.5×1.9×
Chaoying Yang · 1×
Citations per year

Countries citing papers authored by Sinan Li

Since Specialization
Citations

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

Fields of papers citing papers by Sinan Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1
The emerging graph neural networks for intelligent fault diagnostics and prognostics: A guideline and a benchmark study
Hit paper breakdown →
2021445
2 202277
3 202364
4 202358
5 202024
6 202311
7 20214
8 20241
9 20241

About Sinan Li

Sinan Li is a scholar working on Control and Systems Engineering, Artificial Intelligence, Molecular Biology, Mechanical Engineering and Urban Studies, having authored 9 papers that have together received 685 indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (3 papers), Machine Fault Diagnosis Techniques (3 papers), Machine Learning in Bioinformatics (2 papers), Iron and Steelmaking Processes (2 papers), Metallurgical Processes and Thermodynamics (2 papers), Mineral Processing and Grinding (1 paper), Neuroscience and Neural Engineering (1 paper) and Transcranial Magnetic Stimulation Studies (1 paper). The work is most often cited by research in Control and Systems Engineering (458 citations), Medical Laboratory Technology (13 citations), Mechanics of Materials (138 citations), Artificial Intelligence (178 citations) and Safety, Risk, Reliability and Quality (44 citations). Sinan Li has collaborated with scholars based in China, Nigeria and Switzerland. Frequent co-authors include Ruqiang Yan, Tianfu Li, Chuang Sun, Zheng Zhou, Xuefeng Chen, Xuefeng Chen, Zhiying Wang, Yan Yan, Abhishek Kandwal and Olatunji Mumini Omisore. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, steel research international, Frontiers in Bioengineering and Biotechnology, Journal of Manufacturing Systems and Journal of Sustainable Metallurgy.

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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