Sifan Wang
- Statistical and Nonlinear Physics top 0.05%
- Model Reduction and Neural Networks 13
- Computational Mechanics top 0.5%
- Fluid Dynamics and Turbulent Flows 6
- Lattice Boltzmann Simulation Studies 3
- Aerospace Engineering top 1%
- Artificial Intelligence top 1%
-
- Electromagnetic Simulation and Numerical Methods 3
-
- Stellar, planetary, and galactic studies 2
-
- Non-Destructive Testing Techniques 2
-
- Numerical methods for differential equations 2
-
- Numerical methods in engineering 2
- Co-authors
- Paris PerdikarisGeorge Em KarniadakisLu LuIoannis G. KevrekidisLiu YangHanwen WangXinling YuZhicheng Wang
- Cited by
- Statistical and Nonlinear PhysicsComputational MechanicsStatistics, Probability and Uncertainty
- Journals
- The Astrophysical Journal (1 paper)Journal of Computational Physics (3 papers)Science Advances (1 paper)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Sifan Wang
14 papers receiving 6.9k citations
Hit Papers
Peers
Comparison fields: 5 of 159
- Statistical and Nonlinear Physics 3.9k
- Computational Mechanics 1.7k
- Statistics, Probability and Uncertainty 540
- Aerospace Engineering 1.0k
- Artificial Intelligence 1.3k
Countries citing papers authored by Sifan Wang
This map shows the geographic impact of Sifan 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 Sifan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sifan Wang more than expected).
Fields of papers citing papers by Sifan Wang
This network shows the impact of papers produced by Sifan 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 Sifan Wang. The network helps show where Sifan Wang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sifan Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 0 | |
| 7 | 2024 | 0 | |
| 8 | 2024 | 5 | |
| 9 | Respecting causality for training physics-informed neural networksbreakdown → | 2024 | 120 |
| 10 | 2024 | 2 | |
| 11 | 2023 | 17 | |
| 12 | 2022 | 10 | |
| 13 | 2022 | 66 | |
| 14 | 2022 | 67 | |
| 15 | Physics-informed machine learningbreakdown → | 2021 | 3772 |
| 16 | Understanding and Mitigating Gradient Flow Pathologies in Physics-Informed Neural Networksbreakdown → | 2021 | 859 |
| 17 | When and why PINNs fail to train: A neural tangent kernel perspectivebreakdown → | 2021 | 672 |
| 18 | Learning the solution operator of parametric partial differential equations with physics-informed DeepONetsbreakdown → | 2021 | 439 |
| 19 | Physics-Informed Neural Networks for Heat Transfer Problemsbreakdown → | 2021 | 686 |
| 20 | 2020 | 69 |
About Sifan Wang
Sifan Wang is a scholar working on Statistical and Nonlinear Physics, Computational Mechanics and Numerical Analysis, having authored 21 papers that have together received 7.1k indexed citations. Recurring topics across this work include Model Reduction and Neural Networks (13 papers), Fluid Dynamics and Turbulent Flows (6 papers), Lattice Boltzmann Simulation Studies (3 papers), Electromagnetic Simulation and Numerical Methods (3 papers), Stellar, planetary, and galactic studies (2 papers), Non-Destructive Testing Techniques (2 papers), Numerical methods for differential equations (2 papers) and Numerical methods in engineering (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (3.9k citations), Computational Mechanics (1.7k citations) and Statistics, Probability and Uncertainty (540 citations). Sifan Wang has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Paris Perdikaris, George Em Karniadakis, Lu Lu, Ioannis G. Kevrekidis, Liu Yang, Hanwen Wang, Xinling Yu, Zhicheng Wang, Shengze Cai and Shyam Sankaran. Their work appears in journals such as The Astrophysical Journal, Journal of Computational Physics and Science Advances.
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.