Hanwen Wang
About
In The Last Decade
Hanwen Wang
8 papers receiving 874 citations
Hit Papers
Peers
Comparison fields: 5 of 93
- Statistical and Nonlinear Physics 604
- Computational Mechanics 262
- Artificial Intelligence 192
- Aerospace Engineering 149
- Mechanical Engineering 95
Countries citing papers authored by Hanwen Wang
This map shows the geographic impact of Hanwen Wang'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 Hanwen Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hanwen Wang more than expected).
Fields of papers citing papers by Hanwen Wang
This network shows the impact of papers produced by Hanwen Wang. 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 Hanwen Wang. The network helps show where Hanwen Wang may publish in the future.
Co-authorship network of co-authors of Hanwen Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Hanwen Wang. A scholar is included among the top collaborators of Hanwen Wang 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 Hanwen Wang. Hanwen Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 67 | |
| 8 | 36 | |
| 9 | Learning the solution operator of parametric partial differential equations with physics-informed DeepONets breakdown → | 439 |
| 10 | On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks breakdown → | 355 |
| 11 | 1 |
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.