Publications

Notation: * equal contribution; # corresponding author.

Preprints

Mao, R.*, Zhang, R.*, Bai, X., Wu, T., Zhang, T., Chen, Z., Lin, M., Zeng, B., Xu, Y., Xiang, Y., Zhang, H., Goswami, S., Dawe, P. A., Xu, Y., An, Z., Yan, M., Lu, X., Wang, Y., Bai, R., Gao, H., Fang, X., Li, H., Sun, H.#, Chen, Z. X.# (2026). Benchmarking Neural Surrogates on Realistic Spatiotemporal Multiphysics Flows. arXiv preprint arXiv:2512.18595.
Zhang, R., Wan, H., Liu, Y., Sun, H.# (2026). Stable Spectral Neural Operator for Learning Stiff PDE Systems from Limited Data. arXiv preprint arXiv:2512.11686.
Zhang, R., Meng, Q., Wan, H., Liu, Y., Ma, Z-M., & Sun, H. (2026). OmniFluids: Unified Physics Pre-trained Modeling of Fluid Dynamics. arXiv preprint arXiv:2506.10862.

Zhou, H., Xiong, A., Cao, L., Chen, L., Zhang, R., Wang, Q., Liao, Z., Wan, H., Zeng, B., Li, C., Sun, H.#. (2026). Generative Spatial Down-scaling of Global Ocean Wind Speed Profiles via a Diffusion Model. Neurocomputing.
Zeng, B.*, Zhang, R.*, Mao, R., Yan, M., Bai, X., Liu, Y., Chen, Z. X., Sun, H.#. (2026). NPSolver: Neural Poisson Solver with Iterative Physics Supervision. ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Wan, H., Zhang, R.#, & Sun, H. (2026). Spectral-inspired Operator Learning with Limited Data and Unknown Physics. ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Zhou, H., Zhang, R.#, Wan, H., & Sun, H.# (2026). PerFlow: Physics-Embedded Rectified Flow for Efficient Reconstruction and Uncertainty Quantification of Spatiotemporal Dynamics. International Joint Conference on Artificial Intelligence.
Sun, G.*, Miao, T.*, Huang, H., Chen, H., Wan, H., Zhang, R.#, & Sun, H.# (2026). Geometry-Aware Neural Optimizer for Shape Optimization and Inversion. International Conference on Machine Learning.
Wan, H., Wang, Q., Mi, Y., Zhang, R.#, & Sun, H.# (2026). PIMRL: Physics-Informed Multi-Scale Recurrent Learning for Burst-sampled Spatiotemporal Dynamics. Proceedings of the AAAI Conference on Artificial Intelligence.
Du, X.*#, Dou, Q.*, Fan, L., & Zhang, R.# (2026). Flexible Concept Bottleneck Model. Proceedings of the AAAI Conference on Artificial Intelligence.

Wan, H.*, Zhang, R.*, Wang, Q., Liu, Y., & Sun H. (2025). PeSANet: Physics-encoded Spectral Attention Network for Simulating PDE-Governed Complex Systems. International Joint Conference on Artificial Intelligence.
Zhang, R., Meng, Q., Zhu, R., Wang, Y., Shi, W., Zhang, S., Ma, Z.M., & Liu, T.Y. (2025). Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation. IEEE Transactions on Pattern Analysis and Machine Intelligence. Link Code
Zhang, R.*, Du, X.*, Yan, J., & Zhang, S. (2025). The Decoupling Concept Bottleneck Model. IEEE Transactions on Pattern Analysis and Machine Intelligence. Link Code

Zhang, R., Meng, Q., & Ma, Z.M. (2024). Deciphering and Integrating Invariants for Neural Operator Learning with Various Physical Mechanisms. National Science Review. Link Code

Zhang, R., Hu, P., Meng, Q., Wang, Y., Zhu, R., Chen, B., Ma, Z.M., & Liu, T.Y. (2022). DRVN (Deep Random Vortex Network): A New Physics-informed Machine Learning Method for Simulating and Inferring Incompressible Fluid Flows. Physics of Fluids. Link Code
Zhang, R., & Zhang, S. (2022). Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime. In Proceedings of the AAAI Conference on Artificial Intelligence (Oral). Link
Du, X., Yan, J., Zhang, R., & Zha, H. (2022). Cross-network Skip-gram Embedding for Joint Network Alignment and Link Prediction. IEEE Transactions on Knowledge and Data Engineering. Link Code