Lingbin Meng
Impact in
- Automotive Engineering top 5%
- Additive Manufacturing and 3D Printing Technologies
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- Manufacturing Process and Optimization
- Industrial Vision Systems and Defect Detection
- Digital Transformation in Industry
Papers in
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- Additive Manufacturing Materials and Processes 5
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- Silicone and Siloxane Chemistry 2
- Co-authors
- Jing Zhang (6 shared papers)Brandon McWilliams (2 shared papers)William Jarosinski (1 shared paper)Hyeyoung Park (1 shared paper)Yeon‐Gil Jung (1 shared paper)Je-Hyun Lee (1 shared paper)Yi Zhang (2 shared papers)Guang‐Hui Chen (1 shared paper)
- Journals
- JOM (2 papers)Journal of Manufacturing Science and Engineering (1 paper)Biomacromolecules (1 paper)New Journal of Chemistry (1 paper)Molecules (1 paper)
- Partner nations
- ChinaUnited StatesSouth Korea
In The Last Decade
Lingbin Meng
12 papers receiving 467 citations
Lingbin Meng's Hit Papers
Peers
Comparison fields: 5 of 69
- Automotive Engineering 261
- Industrial and Manufacturing Engineering 168
- Mechanical Engineering 349
- Materials Chemistry 77
- Health Informatics 2
Countries citing papers authored by Lingbin Meng
This map shows the geographic impact of Lingbin Meng'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 Lingbin Meng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lingbin Meng more than expected).
Fields of papers citing papers by Lingbin Meng
This network shows the impact of papers produced by Lingbin Meng. 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 Lingbin Meng. The network helps show where Lingbin Meng may publish in the future.
Co-authors
The 25 scholars most cited alongside Lingbin Meng, 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 | Machine Learning in Additive Manufacturing: A Review Hit paper breakdown → | 2020 | 335 |
| 2 | 2019 | 66 | |
| 3 | 2018 | 22 | |
| 4 | 2018 | 12 | |
| 5 | 2018 | 9 | |
| 6 | 2020 | 8 | |
| 7 | 2023 | 7 | |
| 8 | 2022 | 7 | |
| 9 | 2015 | 6 | |
| 10 | 2024 | 4 | |
| 11 | 2023 | 3 | |
| 12 | 2021 | 1 | |
| 13 | 2024 | 0 |
About Lingbin Meng
Lingbin Meng is a scholar working on Mechanical Engineering, Materials Chemistry, Industrial and Manufacturing Engineering, Automotive Engineering and Polymers and Plastics, having authored 13 papers that have together received 480 indexed citations. Recurring topics across this work include Additive Manufacturing Materials and Processes (5 papers), Metal-Organic Frameworks: Synthesis and Applications (2 papers), Synthesis and properties of polymers (2 papers), Manufacturing Process and Optimization (2 papers), Additive Manufacturing and 3D Printing Technologies (2 papers), Silicone and Siloxane Chemistry (2 papers), Crop Yield and Soil Fertility (1 paper) and Membrane Separation Technologies (1 paper). The work is most often cited by research in Automotive Engineering (261 citations), Industrial and Manufacturing Engineering (168 citations), Mechanical Engineering (349 citations), Materials Chemistry (77 citations) and Health Informatics (2 citations). Lingbin Meng has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Jing Zhang, Brandon McWilliams, William Jarosinski, Hyeyoung Park, Yeon‐Gil Jung, Je-Hyun Lee, Yi Zhang, Guang‐Hui Chen, Xiao‐Chun Huang and Yadong Yu. Their work appears in journals such as JOM, Journal of Manufacturing Science and Engineering, Biomacromolecules, New Journal of Chemistry and Molecules.
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.