Jia-Wei Chang
- Environmental Engineering top 5%
- Automotive Engineering top 10%
- Ocean Engineering top 5%
- Enhanced Oil Recovery Techniques 8
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- Stock Market Forecasting Methods 3
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- Pickering emulsions and particle stabilization 6
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- Music and Audio Processing 5
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- Petroleum Processing and Analysis 4
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- Surfactants and Colloidal Systems 3
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- Surface Roughness and Optical Measurements 3
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- Hydrocarbon exploration and reservoir analysis 3
Jia-Wei Chang
57 papers receiving 685 citations
Peers
Comparison fields: 5 of 119
- Environmental Engineering 185
- Health, Toxicology and Mutagenesis 145
- Automotive Engineering 82
- Ocean Engineering 89
- Management Science and Operations Research 70
Countries citing papers authored by Jia-Wei Chang
This map shows the geographic impact of Jia-Wei Chang'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 Jia-Wei Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jia-Wei Chang more than expected).
Fields of papers citing papers by Jia-Wei Chang
This network shows the impact of papers produced by Jia-Wei Chang. 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 Jia-Wei Chang. The network helps show where Jia-Wei Chang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jia-Wei Chang, 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 | 2025 | 5 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 5 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 5 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 8 | |
| 8 | 2024 | 10 | |
| 9 | 2024 | 3 | |
| 10 | 2024 | 7 | |
| 11 | 2023 | 7 | |
| 12 | 2023 | 1 | |
| 13 | 2023 | 6 | |
| 14 | 2022 | 33 | |
| 15 | 2021 | 9 | |
| 16 | A Study on Using Transfer Learning to Improve BERT Model for Emotional Classification of Chinese Lyrics. | 2021 | 1 |
| 17 | Leveraging the Path Signature for Skeleton-based Human Action Recognition. | 2017 | 18 |
| 18 | 2016 | 8 | |
| 19 | Using grammar patterns to evaluate semantic similarity for short texts | 2012 | 4 |
| 20 | A Corpus-Based Statistics-Oriented Transfer and Generation Model for Machine Translation | 1993 | 2 |
About Jia-Wei Chang
Jia-Wei Chang is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Ocean Engineering, having authored 58 papers that have together received 720 indexed citations. Recurring topics across this work include Enhanced Oil Recovery Techniques (8 papers), Pickering emulsions and particle stabilization (6 papers), Music and Audio Processing (5 papers), Petroleum Processing and Analysis (4 papers), Surfactants and Colloidal Systems (3 papers), Surface Roughness and Optical Measurements (3 papers), Hydrocarbon exploration and reservoir analysis (3 papers) and Stock Market Forecasting Methods (3 papers). The work is most often cited by research in Environmental Engineering (185 citations), Health, Toxicology and Mutagenesis (145 citations) and Automotive Engineering (82 citations). Jia-Wei Chang has collaborated with scholars based in Taiwan, China and Japan. Frequent co-authors include Jen-Wei Huang, Jason C. Hung, Ming-Che Lee, Neil Y. Yen, Dasheng Lee, Hairong Wu, Jirui Hou, Wenhao Shao, G. Li and Ning Kang. Their work appears in journals such as Journal of Agricultural and Food Chemistry, Expert Systems with Applications and IEEE Access.
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.