Chenxi Pang
Impact in
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- Recycling and Waste Management Techniques
Papers in
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- Recycling and Waste Management Techniques 3
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- Natural Language Processing Techniques 4
- Topic Modeling 3
- Co-authors
- Mandar Joshi (2 shared papers)Kenton Lee (2 shared papers)Fangyu Liu (2 shared papers)Jujun Ruan (5 shared papers)Yasemin Altün (3 shared papers)Nigel Collier (2 shared papers)Francesco Piccinno (2 shared papers)Julian Martin Eisenschlos (3 shared papers)
- Journals
- ACS Sustainable Chemistry & Engineering (2 papers)Transactions of the Association for Computational Linguistics (1 paper)Resources Conservation and Recycling (1 paper)International Journal of Environmental Research and Public Health (1 paper)Chemical Engineering Journal (1 paper)
- Partner nations
- ChinaUnited KingdomSwitzerland
In The Last Decade
Chenxi Pang
8 papers receiving 81 citations
Peers
Comparison fields: 5 of 33
- Industrial and Manufacturing Engineering 18
- Health Informatics 2
- Computer Vision and Pattern Recognition 28
- Artificial Intelligence 38
- Environmental Engineering 13
Countries citing papers authored by Chenxi Pang
This map shows the geographic impact of Chenxi Pang'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 Chenxi Pang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chenxi Pang more than expected).
Fields of papers citing papers by Chenxi Pang
This network shows the impact of papers produced by Chenxi Pang. 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 Chenxi Pang. The network helps show where Chenxi Pang may publish in the future.
Co-authors
The 23 scholars most cited alongside Chenxi Pang, 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 | 2023 | 23 | |
| 2 | 2023 | 20 | |
| 3 | 2022 | 13 | |
| 4 | 2016 | 10 | |
| 5 | 2024 | 9 | |
| 6 | 2023 | 5 | |
| 7 | 2023 | 5 | |
| 8 | 2023 | 1 | |
| 9 | 2025 | 0 | |
| 10 | 2023 | 0 | |
| 11 | 2025 | 0 |
About Chenxi Pang
Chenxi Pang is a scholar working on Industrial and Manufacturing Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Environmental Engineering and Mechanical Engineering, having authored 11 papers that have together received 86 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (4 papers), Recycling and Waste Management Techniques (3 papers), Multimodal Machine Learning Applications (3 papers), Extraction and Separation Processes (3 papers), Photovoltaic Systems and Sustainability (3 papers), Topic Modeling (3 papers), Metal Extraction and Bioleaching (1 paper) and Membrane Separation Technologies (1 paper). The work is most often cited by research in Industrial and Manufacturing Engineering (18 citations), Health Informatics (2 citations), Computer Vision and Pattern Recognition (28 citations), Artificial Intelligence (38 citations) and Environmental Engineering (13 citations). Chenxi Pang has collaborated with scholars based in China, United Kingdom and Switzerland. Frequent co-authors include Mandar Joshi, Kenton Lee, Fangyu Liu, Jujun Ruan, Yasemin Altün, Nigel Collier, Francesco Piccinno, Julian Martin Eisenschlos, Baojia Qin and Wenhu Chen. Their work appears in journals such as ACS Sustainable Chemistry & Engineering, Transactions of the Association for Computational Linguistics, Resources Conservation and Recycling, International Journal of Environmental Research and Public Health and Chemical Engineering Journal.
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.