Pengcheng He
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Molecular Biology
- Sociology and Political Science
- Co-authors
- Weizhu ChenJianfeng GaoXiaodong LiuYelong ShenJiawei HanYuning MaoHai ZhaoNan Duan
- Topics
- Topic Modeling (16 papers)Natural Language Processing Techniques (14 papers)Multimodal Machine Learning Applications (10 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Pengcheng He
33 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Artificial Intelligence 876
- Computer Vision and Pattern Recognition 224
- Information Systems 124
- Molecular Biology 61
- Sociology and Political Science 47
Countries citing papers authored by Pengcheng He
This map shows the geographic impact of Pengcheng He'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 Pengcheng He with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pengcheng He more than expected).
Fields of papers citing papers by Pengcheng He
This network shows the impact of papers produced by Pengcheng He. 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 Pengcheng He. The network helps show where Pengcheng He may publish in the future.
Co-authorship network of co-authors of Pengcheng He
This figure shows the co-authorship network connecting the top 25 collaborators of Pengcheng He. A scholar is included among the top collaborators of Pengcheng He 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 Pengcheng He. Pengcheng He 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 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 6 | |
| 6 | 12 | |
| 7 | 6 | |
| 8 | 0 | |
| 9 | 19 | |
| 10 | 2 | |
| 11 | 20 | |
| 12 | 13 | |
| 13 | 98 | |
| 14 | DEBERTA: DECODING-ENHANCED BERT WITH DISENTANGLED ATTENTIONbreakdown → | 659 |
| 15 | 21 | |
| 16 | 28 | |
| 17 | 36 | |
| 18 | RESEARCH ADVANCE OF 3-HYDROXY-3-METHYLGLUTARYL-COENZYME A SYNTHASE IN PLANT ISOPRENOID BIOSYNTHESIS | 10 |
| 19 | 2 | |
| 20 | Kinetics and Mechanism of Metal cation Catalysis in the Hydrolysis of p-Nitrophenyl Picolinate (PNPP) | 2 |
About Pengcheng He
Pengcheng He is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Developmental Biology, having authored 40 papers that have together received 1.2k indexed citations. Recurring topics across this work include Topic Modeling (16 papers), Natural Language Processing Techniques (14 papers) and Multimodal Machine Learning Applications (10 papers). The work is most often cited by research in Artificial Intelligence (876 citations), Computer Vision and Pattern Recognition (224 citations) and Health Informatics (13 citations). Pengcheng He has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Weizhu Chen, Jianfeng Gao, Xiaodong Liu, Xiaodong Liu, Yelong Shen, Jiawei Han, Yuning Mao, Hai Zhao, Nan Duan and Yeyun Gong. Their work appears in journals such as Blood, Journal of Materials Chemistry A and Nano Energy.
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.