Pengzhan Jin
- Statistical and Nonlinear Physics top 5%
- Artificial Intelligence top 10%
- Computational Mechanics
- Numerical Analysis top 10%
- Control and Systems Engineering
- Co-authors
- Lu LuShuai MengGeorge Em KarniadakisYifa TangZhen ZhangIoannis G. KevrekidisBo Xiao
- Topics
- Neural Networks and Applications (4 papers)Model Reduction and Neural Networks (4 papers)Tensor decomposition and applications (2 papers)
- Journals
- IEEE Transactions on Neural Networks and Learning SystemsNeural NetworksSIAM Journal on Scientific Computing
- Partner nations
- ChinaUnited States
In The Last Decade
Pengzhan Jin
9 papers receiving 285 citations
Hit Papers
Peers
Comparison fields: 5 of 70
- Statistical and Nonlinear Physics 200
- Artificial Intelligence 102
- Computational Mechanics 51
- Numerical Analysis 39
- Control and Systems Engineering 34
Countries citing papers authored by Pengzhan Jin
This map shows the geographic impact of Pengzhan Jin'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 Pengzhan Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pengzhan Jin more than expected).
Fields of papers citing papers by Pengzhan Jin
This network shows the impact of papers produced by Pengzhan Jin. 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 Pengzhan Jin. The network helps show where Pengzhan Jin may publish in the future.
Co-authorship network of co-authors of Pengzhan Jin
This figure shows the co-authorship network connecting the top 25 collaborators of Pengzhan Jin. A scholar is included among the top collaborators of Pengzhan Jin 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 Pengzhan Jin. Pengzhan Jin 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 | 8 | |
| 3 | 24 | |
| 4 | MIONet: Learning Multiple-Input Operators via Tensor Productbreakdown → | 109 |
| 5 | 4 | |
| 6 | 7 | |
| 7 | 93 | |
| 8 | 1 | |
| 9 | 8 | |
| 10 | 37 |
About Pengzhan Jin
Pengzhan Jin is a scholar working on Computational Mathematics, Statistical and Nonlinear Physics and Algebra and Number Theory, having authored 10 papers that have together received 291 indexed citations. Recurring topics across this work include Neural Networks and Applications (4 papers), Model Reduction and Neural Networks (4 papers) and Tensor decomposition and applications (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (200 citations), Numerical Analysis (39 citations) and Computational Mathematics (2 citations). Pengzhan Jin has collaborated with scholars based in China and United States. Frequent co-authors include Lu Lu, Shuai Meng, George Em Karniadakis, Yifa Tang, Zhen Zhang, Ioannis G. Kevrekidis and Bo Xiao. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Neural Networks and SIAM Journal on Scientific Computing.
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.