Pengcheng Niu

768 citations
90 papers · 520 indexed · h-index 12

Pengcheng Niu

79 papers receiving 458 citations

Peers

Pengcheng Niu
Comparison fields: 5 of 35
  • Applied Mathematics 418
  • Mathematical Physics 204
  • Modeling and Simulation 88
  • Computational Theory and Mathematics 206
  • Geometry and Topology 22
Replace María Ángeles Rodríguez‐Bellido with:
María Ángeles Rodríguez‐Bellido Spain
Salvador Moll Spain
Ki-Ahm Lee South Korea
Nikos I. Kavallaris United Kingdom
Zhengce Zhang China
Ignacio Guerra Chile
Renate Schaaf United States
Amir Moradifam Canada
Zuodong Yang China
Shouming Zhou China
Pengcheng Niu relative to María Ángeles Rodríguez‐Bellido Spain María Ángeles Rodríguez‐Bellido's profile →
Citations per field
00.5×2.7×
María Ángeles Rodríguez‐Bellido · 1×
Citations per year

Countries citing papers authored by Pengcheng Niu

Since Specialization
Citations

This map shows the geographic impact of Pengcheng Niu'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 Niu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pengcheng Niu more than expected).

Fields of papers citing papers by Pengcheng Niu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pengcheng Niu. 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 Niu. The network helps show where Pengcheng Niu may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Pengcheng Niu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Pengcheng Niu Line = papers co-authored together Pengcheng Niu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20209
3 20208
4 20161
5 20163
6 20159
7 20147
8 20121
9 201214
10 20123
11 20110
12 20115
13 20091
14 20092
15 20088
16
A Hopf Type Principle and a Strong Maximum Principle for the p-Sub-Laplacian on the Group of Heisenberg Type
20071
17 20061
18
PICONE IDENTITY AND HARDY INEQUALITY FOR A CLASS OF VECTOR FIELDS
20033
19 200165
20 19993

About Pengcheng Niu

Pengcheng Niu is a scholar working on Applied Mathematics, Mathematical Physics and Computational Theory and Mathematics, having authored 90 papers that have together received 520 indexed citations. Recurring topics across this work include Nonlinear Partial Differential Equations (62 papers), Advanced Mathematical Modeling in Engineering (31 papers), Advanced Harmonic Analysis Research (29 papers), Advanced Mathematical Physics Problems (27 papers), Nonlinear Differential Equations Analysis (21 papers), Differential Equations and Boundary Problems (17 papers), Geometric Analysis and Curvature Flows (11 papers) and Numerical methods in inverse problems (8 papers). The work is most often cited by research in Applied Mathematics (418 citations), Mathematical Physics (204 citations) and Modeling and Simulation (88 citations). Pengcheng Niu has collaborated with scholars based in China, Italy and United States. Frequent co-authors include Huiqing Zhang, Yong Wang, Leyun Wu, Pengyan Wang, Jingbo Dou, Mei Yu, Maochun Zhu, Ran Zhuo, Maosen Fu and Yan Feng. Their work appears in journals such as Journal of Mathematical Analysis and Applications, Ceramics International and Applied Mathematics and Computation.

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.

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