Submitted & in preparation

1. Wang, X., Du, P., Taneja K., Doon-Ralls, J., Reátegui, E., & Holland, M. (2026). Discovery of Self-Limiting Neutrophil Swarming Using Bayesian Physics-Informed Neural Network. (Submitting soon)

2. Guo, J., Du, P., & Wang, J. X. (2026). Separable Conditional Neural Fields for In-Situ Compression of High-Fidelity Spatiotemporal Turbulence Simulation Data. (Submitting soon)

3. Du, P., Xu, M., Li, Y., & Wang, J. X. (2026). DiFVM: A Vectorized Graph-Based Finite Volume Solver for Differentiable CFD on Unstructured Meshes. arXiv preprint arXiv:2603.15920 (2026). (Under review at Journal of Computational Physics)

4. Du, P., Xu, M., Zhu X., & Wang, J. X. (2026). HUG-VAS: A Hierarchical NURBS-Based Generative Model for Aortic Geometry Synthesis and Controllable Editing. arXiv preprint arXiv:2507.11474. (Submitted to CMAME. Submission Date: 03/19/2026)

5. An, D., Du, P., Wang, J. X., & Wang C. (2026). TSGDiff: Text-Guided Diffusion via Segmentation Priors for Volumetric Medical Image Synthesis (Submitted to MICCAI 2026. Submission Date: 02/13/2026)

Published (as leading author)

1. Du, P., An, D., Wang, C., & Wang, J. X. (2025). AI-Powered Automated Model Construction for Patient-Specific CFD Simulations of Aortic Flows. Science Advances, 11(36), eadw2825. 

2. Du, P., Parikh, M. H., Fan, X., Liu, X. Y., & Wang, J. X. (2024). Conditional neural field latent diffusion model for generating spatiotemporal turbulence. Nature Communications, 15(1), 10416.

3. Du, P., & Wang, J. X. (2022). Reducing Geometric Uncertainty in Computational Hemodynamics by Deep Learning-Assisted Parallel-Chain MCMC. Journal of Biomechanical Engineering, 144(12), 121009.

4. Du, P., Zhu, X., & Wang, J. X. (2022). Deep learning-based surrogate model for three-dimensional patient-specific computational fluid dynamics. Physics of Fluids, 34(8).

5. Du, P., & Agarwal, R. K. (2017). Drag Prediction of NASA Common Research Models Using Different Turbulence Models. In 35th AIAA Applied Aerodynamics Conference (p. 4233).

6. Du, P., & Agarwal, R. K. (2019). Numerical drag prediction of NASA Common Research Models using different turbulence models. Computers & Fluids, 191, 104238.

Published (as contributing author)

7. Guo, J., Du, P., & Wang, J. X. (2026). Conditional Neural Field for Spatial Dimensionality Reduction of Turbulence Data: A Comparison Study. Physics of Fluids, 38(2).

8. Zhou, J., Li, R., Shang, W., Liu, Y, Panda, J. P., Du, P., Liu X., Liang J., Ma, B., Wang, J. X., & Luo, T. (2025). Physics-Informed Neural Networks with Hard-Encoded Angle-Dependent Boundary Conditions for Phonon Boltzmann Transport Equation. Materials Today Physics. 101922. 

9. An, D., Du, P., Wang, J. X., & Wang C. (2025) AortaDiff: Volume-Guided Conditional Diffusion Models for Multi-Branch Aortic Surface Generation. IEEE Transactions on Visualization and Computer Graphics. (2025)

10. Shang, W., Zhou, J., Panda, J. P., Xu, Z., Liu, Y., Du, P., Wang J. X., & Luo, T. (2025). JAX-BTE: A GPU-Accelerated Differentiable Solver for Phonon Boltzmann Transport Equations. npj Computational Materials, 11(1), 129.

11. Akhare, D., Du, P., Luo, T., & Wang, J. X. (2025). Implicit Neural Differential Model for Spatiotemporal Dynamics. Computer Methods in Applied Mechanics and Engineering, 446(Part B), 118280. https://doi.org/10.1016/j.cma.2025.118280

12. An, D., Du, P., Gu, P., Wang, J. X., & Wang, C. (2025). Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation. In 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI) (pp. 1-5). IEEE.

13. Prashanth, M., Du, P., Wang, J. X., & Wu, H. (2024). A neural network-based algorithm for the reconstruction and filtering of single particle trajectory in magnetic particle tracking. Review of Scientific Instruments, 95(5).

14. Prashanth, M. N., Du, P., Wang, J. X., & Wu, H. (2022). AI-based Hybrid Model for Denoising Particle Trajectories Reconstructed from Magnetic Particle Tracking Method. In AIAA SCITECH 2022 Forum (p. 1162).

15. Corpuz, A. M., Jaiswal, M., Du, P., Ramachandra, A. B., Wang, J. X., & Hsu, M. C. (2025). Direct medical image to simulation using auto-segmentation and point cloud-based CFD. Advances in Computational Science and Engineering, 3, 95-124.

16. Liu, X. Y., Parikh, M. H., Fan, X., Du, P., Wang, Q., Chen, Y. F., & Wang, J. X. (2024). CoNFiLD-inlet: Synthetic Turbulence Inflow Using Generative Latent Diffusion Models with Neural Fields. arXiv preprint arXiv:2411.14378. (Accepted by Physical Review Fluids)

17. Sun, L., Du, P., Sun, H., & Wang, J. X. (2022). Group sparse Bayesian learning for data-driven discovery of explicit model forms with multiple parametric datasets. Numerical Algebra, Control and Optimization.

18. Wu, H., Du, P., Kokate, R., & Wang, J. X. (2021). A semi-analytical solution and AI-based reconstruction algorithms for magnetic particle tracking. Plos one, 16(7), e0254051.

19. Wang, X., Yablonsky, G. S., ur Rahman, Z., Yang, Z., Du, P., Tan, H., & Axelbaum, R. L. (2021). Assessment of sulfur trioxide formation due to enhanced interaction of nitrogen oxides and sulfur oxides in pressurized oxy-combustion. Fuel, 290, 119964.

20. Wang, X., Adeosun, A., Yablonsky, G., Gopan, A., Du, P., & Axelbaum, R. L. (2018). Synergistic SO x/NO x chemistry leading to enhanced SO 3 and NO 2 formation during pressurized oxy-combustion. Reaction Kinetics, Mechanisms and Catalysis, 123, 313-322.

•      Presenter (Invited seminar talk) Pan Du. “AI-powered automated model construction for patient-specific CFD simulations of aortic flows”, Dr. Ching-Long Lin’s lab at University of Iowa. 

•     Chair Host (Incoming Invited Chair Host) Pan Du. Biological Fluid Dynamics: Cardiac Flow II, 78rd Annual Meeting of the APS Division of Fluid Dynamics, Nov 23–25, 2020, Houston Texas. 

•    Presenter (Invited seminar talk) Pan Du. “HUG-VAS: A Hierarchical NURBS Generative Model for Aortic Vascular Geometry Synthesis.” USACM Student Chapter Seminar Series, Oct 26, 2025, online. 

•     Presenter (Invited seminar talk): Pan Du. “CoNFiLD: Conditional Neural Field Latent Diffusion Model Generating Spatiotemporal Turbulence.” Frontiers in Scientific Machine Learning (FSML) Seminar Series, University of Michigan.

•      USNCCM18 Best Poster Award (Top 10%), July 20-24, 2025, USACM Administrative

•      USNCCM18 Conference 2025 Student Travel Award, July 20-24, 2025, USACM Administrative

•      UQ-MLIP Conference 2024 Student Travel Award, USACM Administrative

•      2022 SES Annual Technical Conference Student Travel Award, Society of Engineering Science

•      USNCCM16 Conference Award, July 25-29, 2021, Ruth Hengest, USACM Administrative

•      Poster session award (2nd in 30), Fall Symposium, Oct 27, 2021, Lucy Family Institute for Data and Society

•      Top 10 of the Final of Electronic Information Contest, college level at Tsinghua University

•      First prize of 2011 Chinese Physics Olympiad (CPhO) Shaanxi district, China, State level (Top 0.6%)

Reviewed Journals

•      AI Thermal Fluids

•      Biomedical Physics & Engineering Express

•      Engineering Research Express

•      Nature Scientific Reports

•      Npj Digital Medicine

•      Journal of Heat and Mass Transfer

•      Journals of Computational Physics 

•      Physica Scripta

•      Physiological Measurement

•      Physics of Fluids

•      SoftwareX

•      Theoretical and applied mechanics letters