Sifan Wang

11.7k total citations · 7 hit papers
21 papers, 7.1k citations indexed

About

Sifan Wang is a scholar working on Statistical and Nonlinear Physics, Computational Mechanics and Mechanical Engineering. According to data from OpenAlex, Sifan Wang has authored 21 papers receiving a total of 7.1k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Statistical and Nonlinear Physics, 9 papers in Computational Mechanics and 3 papers in Mechanical Engineering. Recurrent topics in Sifan Wang's work include Model Reduction and Neural Networks (13 papers), Fluid Dynamics and Turbulent Flows (6 papers) and Lattice Boltzmann Simulation Studies (3 papers). Sifan Wang is often cited by papers focused on Model Reduction and Neural Networks (13 papers), Fluid Dynamics and Turbulent Flows (6 papers) and Lattice Boltzmann Simulation Studies (3 papers). Sifan Wang collaborates with scholars based in United States, China and Canada. Sifan Wang's 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 and has published in prestigious journals such as The Astrophysical Journal, Journal of Computational Physics and Science Advances.

In The Last Decade

Sifan Wang

14 papers receiving 6.9k citations

Hit Papers

Physics-informed machine learning 2021 2026 2022 2024 2021 2021 2021 2021 2021 1000 2.0k 3.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Physics-informed machine learning
    2021 3.8k citations George Em Karniadakis, Ioannis G. Kevrekidis et al. Nature Reviews Physics profile →
  2. Understanding and Mitigating Gradient Flow Pathologies in Physics-Informed Neural Networks
    2021 859 citations Sifan Wang, Paris Perdikaris et al. SIAM Journal on Scientific Computing profile →
  3. Physics-Informed Neural Networks for Heat Transfer Problems
    2021 686 citations Shengze Cai, Zhicheng Wang et al. Journal of Heat Transfer profile →
  4. When and why PINNs fail to train: A neural tangent kernel perspective
    2021 672 citations Sifan Wang, Xinling Yu et al. Journal of Computational Physics profile →
  5. Learning the solution operator of parametric partial differential equations with physics-informed DeepONets
    2021 439 citations Sifan Wang, Hanwen Wang et al. Science Advances profile →
  6. On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks
    2021 355 citations Sifan Wang, Hanwen Wang et al. Computer Methods in Applied Mechanics and Engineering profile →
  7. Respecting causality for training physics-informed neural networks
    2024 120 citations Sifan Wang, Shyam Sankaran et al. Computer Methods in Applied Mechanics and Engineering profile →

Peers

Sifan Wang
Lu Lu United States
Gianluigi Rozza Italy
Maziar Raissi United States
Ameya D. Jagtap United States
Igor Mezić United States
Shengze Cai China
Nicholas Zabaras United States
Gang Hu China
Xuhui Meng China
Lu Lu United States
Sifan Wang
Citations per year, relative to Sifan Wang Sifan Wang (= 1×) peers Lu Lu

Countries citing papers authored by Sifan Wang

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Sifan Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Sifan Wang. A scholar is included among the top collaborators of Sifan 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 Sifan Wang. Sifan Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cui, Chuanjie, et al.. (2025). Sharp-PINNs: Staggered hard-constrained physics-informed neural networks for phase field modelling of corrosion. Computer Methods in Applied Mechanics and Engineering. 447. 118346–118346.
2.
Wang, Sifan, et al.. (2025). Micrometer: Micromechanics transformer for predicting full field mechanical responses of heterogeneous materials. Computer Methods in Applied Mechanics and Engineering. 448. 118373–118373.
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Wang, Sifan, et al.. (2024). Enhanced DGTD Method Using RCM Unit Reorder Technique. 1–3.
8.
Fang, Zhiwei, Sifan Wang, & Paris Perdikaris. (2024). Learning Only on Boundaries: A Physics-Informed Neural Operator for Solving Parametric Partial Differential Equations in Complex Geometries. Neural Computation. 36(3). 475–498. 5 indexed citations
9.
Wang, Sifan, Shyam Sankaran, & Paris Perdikaris. (2024). Respecting causality for training physics-informed neural networks. Computer Methods in Applied Mechanics and Engineering. 421. 116813–116813. 120 indexed citations breakdown →
10.
Dong, Ruobing, et al.. (2024). Disk2Planet: A Robust and Automated Machine Learning Tool for Parameter Inference in Disk–Planet Systems. The Astrophysical Journal. 976(2). 200–200. 2 indexed citations
11.
Dong, Ruobing, et al.. (2023). PPDONet: Deep Operator Networks for Fast Prediction of Steady-state Solutions in Disk–Planet Systems. The Astrophysical Journal Letters. 950(2). L12–L12. 17 indexed citations
12.
Zhou, Yong, Sifan Wang, Jiaqi Zhao, Hancheng Zhu, & Rui Yao. (2022). Fine-Grained Feature Enhancement for Object Detection in Remote Sensing Images. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 10 indexed citations
13.
Wang, Sifan & Paris Perdikaris. (2022). Long-time integration of parametric evolution equations with physics-informed DeepONets. Journal of Computational Physics. 475. 111855–111855. 66 indexed citations
14.
Wang, Sifan, Hanwen Wang, & Paris Perdikaris. (2022). Improved Architectures and Training Algorithms for Deep Operator Networks. Journal of Scientific Computing. 92(2). 67 indexed citations
15.
Karniadakis, George Em, Ioannis G. Kevrekidis, Lu Lu, et al.. (2021). Physics-informed machine learning. Nature Reviews Physics. 3(6). 422–440. 3772 indexed citations breakdown →
16.
Wang, Sifan, et al.. (2021). Understanding and Mitigating Gradient Flow Pathologies in Physics-Informed Neural Networks. SIAM Journal on Scientific Computing. 43(5). A3055–A3081. 859 indexed citations breakdown →
17.
Wang, Sifan, Xinling Yu, & Paris Perdikaris. (2021). When and why PINNs fail to train: A neural tangent kernel perspective. Journal of Computational Physics. 449. 110768–110768. 672 indexed citations breakdown →
18.
Wang, Sifan, Hanwen Wang, & Paris Perdikaris. (2021). Learning the solution operator of parametric partial differential equations with physics-informed DeepONets. Science Advances. 7(40). eabi8605–eabi8605. 439 indexed citations breakdown →
19.
Cai, Shengze, Zhicheng Wang, Sifan Wang, Paris Perdikaris, & George Em Karniadakis. (2021). Physics-Informed Neural Networks for Heat Transfer Problems. Journal of Heat Transfer. 143(6). 686 indexed citations breakdown →
20.
Wang, Sifan & Paris Perdikaris. (2020). Deep learning of free boundary and Stefan problems. Journal of Computational Physics. 428. 109914–109914. 69 indexed citations

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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2026