Refereed Publications
Underlined names are my students. † means equal contributions.
  1. FoamGPT: A Fine-Tuned Language Model for Automation of CFD Simulations with OpenFOAM
    Ling Yue, Peijing Xu, Tingwen Zhang, Nithin Somasekharan, Shaowu Pan
    NeurIPS Workshop ML4PS (2025)
    [Paper]
  2. Foam-Agent: Towards Automated Intelligent CFD Workflows
    Ling Yue, Nithin Somasekharan, Yadi Cao, Shaowu Pan
    NeurIPS Workshop ML4PS (2025)
    [Paper]
  3. Code2MCP: Transforming Code Repositories into MCP Services
    Chaoqian Ouyang†, Ling Yue†, Shimin Di, Libin Zheng, Linan Yue, Shaowu Pan, Jian Yin, Min-Ling Zhang
    NeurIPS Workshop SEA (2025)
    [Paper]
  4. UniFoil: A Universal Dataset of Airfoils in Transitional and Turbulent Regimes for Subsonic and Transonic Flows
    Rohit Sunil Kanchi, Benjamin Melanson, Nithin Somasekharan, Shaowu Pan, Sicheng He
    NeurIPS (2025)
    [Paper]
  5. Learning Noise-Robust Stable Koopman Operator for Control With Hankel DMD
    Shahriar Akbar Sakib, Shaowu Pan
    IEEE Transactions on Control Systems Technology (2025)
    [Paper] [Code]
  6. Beyond the Kolmogorov Barrier: A Learnable Weighted Hybrid Autoencoder for Model Order Reduction
    Nithin Somasekharan, Shaowu Pan
    Proceedings of the Royal Society A (2025)
    [Paper] [Code]
  7. Surrogate modeling of heat transfer under flow fluctuation conditions using Fourier Basis-Deep Operator Network with uncertainty quantification
    Qiyun Cheng, Md Hossain Sahadath, Huihua Yang, Shaowu Pan, Wei Ji
    Progress in Nuclear Energy (2025)
    [Paper]
  8. On the lifting and reconstruction of nonlinear systems with multiple invariant sets
    Shaowu Pan, Karthik Duraisamy
    Nonlinear Dynamics (2024)
    [Paper] [Code]
  9. Grad–Shafranov equilibria via data-free physics informed neural networks
    Byoungchan Jang, Alan A. Kaptanoglu, Rahul Gaur, Shaowu Pan, Matt Landreman, William Dorland
    Physics of Plasmas (2024)
    [Paper]
  10. PyKoopman: A Python Package for Data-Driven Approximation of the Koopman Operator
    Shaowu Pan, Eurika Kaiser, Brian M. de Silva, Nathan Kutz, Steven L. Brunton
    Journal of Open Source Software (2024)
    [Paper] [Code]
  11. Neural Implicit Flow: a mesh-agnostic dimensionality reduction paradigm of spatio-temporal data
    Shaowu Pan, Steven Brunton, Nathan Kutz
    Journal of Machine Learning Research (2023)
    [Paper] [Code] [Project Page]
  12. Particle reconstruction of volumetric particle image velocimetry with strategy of machine learning
    Qi Gao, Shaowu Pan, Hongping Wang, Runjie Wei, and Jinjun Wang
    Advances in Aerodynamics (2021)
    [Paper]
  13. Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics
    Weiqi Ji, Weilun Qiu, Zhiyu Shi, Shaowu Pan, and Sili Deng
    Journal of Physical Chemistry A (2021)
    [Paper]
  14. Sparsity-promoting algorithms for the discovery of informative Koopman invariant subspaces
    Shaowu Pan, Nicholas Arnold-Medabalimi, and Karthik Duraisamy
    Journal of Fluid Mechanics (2021)
    [Paper] [Code]
  15. On the Structure of Time-delay Embedding in Linear Models of Non-linear Dynamical Systems
    Shaowu Pan, and Karthik Duraisamy
    Chaos: An Interdisciplinary Journal of Nonlinear Science (2020)
    [Paper]
  16. Physics-Informed Probabilistic Learning of Linear Embeddings of Non-linear Dynamics With Guaranteed Stability
    Shaowu Pan, and Karthik Duraisamy
    SIAM Journal on Applied Dynamical Systems (2020)
    [Paper] [Code]
  17. Surrogate Modeling for Fluid Flows Based on Physics-Constrained Deep Learning Without Simulation Data
    Luning Sun, Han Gao, Shaowu Pan, and Jian-Xun Wang
    Computer Methods in Applied Mechanics and Engineering (2020)
    [Paper]
  18. Prediction of Aerodynamic Flow Fields Using Convolutional Neural Networks
    Saakaar Bhatnagar, Yaser Afshar, Shaowu Pan, Karthik Duraisamy, and Shailendra Kaushik
    Computational Mechanics (2019)
    [Paper]
  19. Long-time predictive modeling of nonlinear dynamical systems using neural networks
    Shaowu Pan, and Karthik Duraisamy
    Complexity (2018) (invited)
    [Paper]
  20. Data-driven Discovery of Closure Models
    Shaowu Pan, and Karthik Duraisamy
    SIAM Journal on Applied Dynamical Systems (2018)
    [Paper] [Code]
  21. The role of bulk viscosity on the decay of compressible, homogeneous, isotropic turbulence
    Shaowu Pan, and Eric Johnsen
    Journal of Fluid Mechanics (2017)
    [Paper]
  22. Combustion Heat-Release Effects on Supersonic Compressible Turbulent Boundary Layers
    Zhenxun Gao, Chongwen Jiang, Shaowu Pan, and Chun-Hian Lee
    AIAA Journal (2015)
    [Paper]
  23. Numerical investigation of rarefaction effects in the vicinity of a sharp leading edge
    Shaowu Pan, Zhenxun Gao, and Chunhian Lee
    AIP Conference Proceedings (2014)
    [Paper]
  24. Characterizing and improving predictive accuracy in shock-turbulent boundary layer interactions using data-driven models
    Anand Pratap Singh, Shaowu Pan, and Karthik Duraisamy
    55th AIAA Aerospace Sciences Meeting (2017)
    [Paper]
  25. Augmentation of turbulence models using field inversion and machine learning
    Karthik Duraisamy, Anand Pratap Singh, and Shaowu Pan
    55th AIAA Aerospace Sciences Meeting (2017)
    [Paper]
  26. An extended CFD model to predict the pumping curve in low pressure plasma etch chamber
    Ning Zhou, Yuanhao Wu, Wenbin Han, and Shaowu Pan
    AIP Conference Proceedings (2014)
    [Paper]
Academic Service