www.panai4science.com

About简介

I am an incoming Assistant Professor in the Department of Mechanical Engineering at Iowa State University, where I will establish the Physics & Health via AI and Shape Emulation (PHASE) Lab in Fall 2027. I am currently a postdoctoral researcher at the University of California, Berkeley, working with Prof. Shawn Shadden.

我将于 2027 年秋季加入爱荷华州立大学（Iowa State University）机械工程系担任助理教授，并创立 PHASE Lab（Physics & Health via AI and Shape Emulation）。实验室致力于人工智能、计算物理与几何建模的交叉研究。

My research background has evolved from classical thermal-fluid sciences to modern scientific machine learning. I received my B.S. in Thermal Engineering from Tsinghua University, where I gained research experience in combustion. During my M.S. in Mechanical Engineering at Washington University in St. Louis, I studied turbulence modeling under the guidance of Prof. Ramesh Agarwal. I later focused on scientific machine learning during my Ph.D. in Aerospace and Mechanical Engineering at the University of Notre Dame under the guidance of Prof. Jian-Xun Wang.

我本科毕业于清华大学，随后在圣路易斯华盛顿大学师从 Ramesh Agarwal 教授获得硕士学位。我在圣母大学航空航天与机械工程专业师从 Jian-Xun Wang 教授获得博士学位，目前在加州大学伯克利分校 Shawn Shadden 教授课题组从事博士后研究。

My research program integrates scientific machine learning, computational fluid dynamics, and geometric modeling to create scalable tools for many-query analysis and digital twins of PDE-governed systems. These methods support applications ranging from cardiovascular biomechanics to broader multiphysics problems. Through the PHASE Lab, I aim to advance AI-enabled modeling and simulation technologies that accelerate discovery and innovation across the physical and biomedical sciences.

我的研究融合人工智能（AI）、计算流体力学（CFD）与几何建模，致力于构建面向复杂偏微分方程（PDE）系统的智能计算框架，支持大规模参数分析、优化设计、不确定性量化以及数字孪生技术。相关方法已应用于心血管生物力学研究，并可进一步推广至更广泛的多物理场问题。未来，PHASE Lab 将持续探索人工智能与几何建模技术的前沿发展方向，推动物理科学与生物医学科学领域的交叉创新。

Academic Appointments学术任职

Incoming Assistant Professor (Fall 2027)候任助理教授（2027 年秋季）Iowa State University logoIowa State University爱荷华州立大学
Postdoctoral Researcher (current)博士后研究员（现任）University of California, Berkeley logoUniversity of California, Berkeley加州大学伯克利分校

Education教育经历

Ph.D., Aerospace and Mechanical Engineering博士，航空航天与机械工程University of Notre Dame logoUniversity of Notre Dame圣母大学
M.S., Mechanical Engineering硕士，机械工程Washington University in St. Louis logoWashington University in St. Louis圣路易斯华盛顿大学
B.S., Thermal Engineering本科，热能工程Tsinghua University logoTsinghua University清华大学
Artificial intelligence, geometry modeling, and computational physics research focus diagram

Research projects研究项目

Medical image segmentation pipeline with uncertainty visualization

AI-powered image segmentation with uncertainty quantification融合不确定性量化的 AI 医学图像分割

Animated vascular geometry generation result

Generative modeling for vascular geometry血管几何的生成式AI建模

Animated cross-patient vascular shape registration

Cross-patient shape registration跨患者形状配准

Animated differentiable fluid mechanics simulation

Differentiable modeling for fluid mechanics流体力学可微分计算模型

Animated turbulence field generated by AI model

Generative AI for turbulence modeling面向湍流建模的生成式 AI

Animated semi-automatic image segmentation workflow

Semi-automatic image segmentation半自动AI医学图像分割

Large-scale aerodynamics and turbulence combustion examples

Large-scale computational physics大规模计算物理

Contact联系方式

Email:邮箱： panai4health@berkeley.edu

Phone:电话： 5748009663

Affiliation:单位： University of California, Berkeley加州大学伯克利分校 2167 Etcheverry Hall, Berkeley, CA 94720

Download CV下载简历

© 2026 Pan Du. All rights reserved.© 2026 杜攀。保留所有权利。

Last updated: October 14, 2026最后更新：2026 年 10 月 14 日

Curriculum Vitae

View my full academic curriculum vitae or download a copy.在线查看或下载我的完整学术简历。

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© 2026 Pan Du. All rights reserved.© 2026 杜攀。保留所有权利。

Last updated: October 14, 2026最后更新：2026 年 10 月 14 日

Publications论文发表

Preprints预印本

  1. Wang, X., Du, P., Taneja, K., Doon-Ralls, J., Reátegui, E., & Holland, M. (2026). Inference of Self-Limiting Neutrophil Swarming Dynamics Using Bayesian Physics-Informed Neural Networks. Submitted to PLOS Computational Biology.
  2. An, D., Du, P., Wang, J. X., & Wang, C. (2027). TSGDiff: Text-Guided Diffusion via Segmentation Priors for Volumetric Medical Image Synthesis. Submitted to AAAI 2027.
  3. Feng, Z., Liu, X. Y., Parikh, M. H., Guo, J., Du, P., Yan, B., & Wang, J. X. (2025). Generative latent diffusion model for inverse modeling and uncertainty analysis in geological carbon sequestration. arXiv preprint arXiv:2508.16640.

Published已发表

  1. Du, P., Li, Y., Xu, M., & Wang, J. X. (2027). DiFVM: A vectorized graph-based finite volume solver for differentiable CFD on unstructured meshes. Journal of Computational Physics, 569(Part 1), 115429.
  2. 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. Computer Methods in Applied Mechanics and Engineering, 462, 119309.
  3. 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).
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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).
  13. 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.
  14. 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.
  15. 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).
  16. 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).
  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. Du, P., & Agarwal, R. K. (2019). Numerical drag prediction of NASA Common Research Models using different turbulence models. Computers & Fluids, 191, 104238.
  21. 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.
  22. Du, P., & Agarwal, R. K. (2017). Drag Prediction of NASA Common Research Models Using Different Turbulence Models. 35th AIAA Applied Aerodynamics Conference.

© 2026 Pan Du. All rights reserved.© 2026 杜攀。保留所有权利。

Last updated: October 14, 2026最后更新：2026 年 10 月 14 日

Course cover for Introduction to Artificial Intelligence

AME40411 Introduction to Artificial IntelligenceAME40411 人工智能导论

Course Instructor, undergraduate level, Fall 2025, 3 credits.课程教师，本科生课程，2025 年秋季，3 学分。

Download syllabus下载课程大纲

My teaching philosophy emphasizes integrating modern AI methods with physical intuition and engineering principles. I aim to help students develop both theoretical understanding and practical problem-solving skills for next-generation computational engineering.

我的教学理念是将现代人工智能方法与物理直觉和工程原理有机结合，帮助学生建立扎实的理论基础，并培养解决实际问题的能力，为下一代计算工程的发展做好准备。

© 2026 Pan Du. All rights reserved.© 2026 杜攀。保留所有权利。

Last updated: October 14, 2026最后更新：2026 年 10 月 14 日

Contact联系方式

For research inquiries, collaboration opportunities, or questions about the PHASE Lab, please get in touch.如需咨询研究合作或 PHASE Lab 相关事宜，欢迎与我联系。

Emailpanai4health@berkeley.edu

Phone+1 574 800 9663

Current affiliationUniversity of California, Berkeley

Address2167 Etcheverry Hall, Berkeley, CA 94720

Lab websitePHASE Lab (www.panai4health.com)