Jianpeng Cheng
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 10%
- Signal Processing top 10%
- Electrical and Electronic Engineering
- Co-authors
- Mirella LapataLi DongDimitri KartsaklisXingxing ZhangJi-Rong WenZhongyuan WangSiva ReddyVijay Saraswat
- Topics
- Natural Language Processing Techniques (12 papers)Topic Modeling (11 papers)Multimodal Machine Learning Applications (4 papers)
- Journals
- The International Journal of Advanced Manufacturing TechnologyComputational LinguisticsOptik
- Partner nations
- United KingdomChinaUnited States
In The Last Decade
Jianpeng Cheng
14 papers receiving 839 citations
Hit Papers
Peers
Comparison fields: 5 of 99
- Artificial Intelligence 612
- Computer Vision and Pattern Recognition 247
- Information Systems 88
- Signal Processing 64
- Electrical and Electronic Engineering 46
Countries citing papers authored by Jianpeng Cheng
This map shows the geographic impact of Jianpeng Cheng'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 Jianpeng Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jianpeng Cheng more than expected).
Fields of papers citing papers by Jianpeng Cheng
This network shows the impact of papers produced by Jianpeng Cheng. 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 Jianpeng Cheng. The network helps show where Jianpeng Cheng may publish in the future.
Co-authorship network of co-authors of Jianpeng Cheng
This figure shows the co-authorship network connecting the top 25 collaborators of Jianpeng Cheng. A scholar is included among the top collaborators of Jianpeng Cheng based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jianpeng Cheng. Jianpeng Cheng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 9 | |
| 4 | 6 | |
| 5 | 24 | |
| 6 | 13 | |
| 7 | 8 | |
| 8 | 8 | |
| 9 | 26 | |
| 10 | 51 | |
| 11 | 3 | |
| 12 | Long Short-Term Memory-Networks for Machine Readingbreakdown → | 664 |
| 13 | 6 | |
| 14 | 32 | |
| 15 | 30 |
About Jianpeng Cheng
Jianpeng Cheng is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Instrumentation, having authored 15 papers that have together received 881 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (12 papers), Topic Modeling (11 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Artificial Intelligence (612 citations), Computer Vision and Pattern Recognition (247 citations) and Signal Processing (64 citations). Jianpeng Cheng has collaborated with scholars based in United Kingdom, China and United States. Frequent co-authors include Mirella Lapata, Li Dong, Dimitri Kartsaklis, Xingxing Zhang, Ji-Rong Wen, Zhongyuan Wang, Siva Reddy, Vijay Saraswat, Zheng Chen and Jun Yan. Their work appears in journals such as The International Journal of Advanced Manufacturing Technology, Computational Linguistics and Optik.
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.