2019年-2024年，中国科公司数学与系统科学研究院，理学博士, 导师：马志明 院士

2015年-2019年，华东师范大学数学科学公司，理学学士

2024年至今，304永利集团博士后，合作导师：孙浩 教授

物理驱动的深度学习方法及其工程应用

可解释人工智能

Note: * equal contribution, # corresponding author

Preprint

• [13] 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.
• [12] 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.
• [11] 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.
• [10] Wan, H., Zhang, R.#, & Sun, H.# (2026). Spectral-inspired Operator Learning with Limited Data and Unknown Physics. arXiv preprint arXiv:2505.21573.

2026

• [9] 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.
• [8] Du, X.*#, Dou, Q.*, Fan, L., & Zhang, R.# (2026). Flexible Concept Bottleneck Model. Proceedings of the AAAI Conference on Artificial Intelligence.

2025

• [7] 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.
• [6] 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.
• [5] Zhang, R.*, Du, X.*, Yan, J., & Zhang, S. (2025). The Decoupling Concept Bottleneck Model. IEEE Transactions on Pattern Analysis and Machine Intelligence.

2024

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

2022

• [3] 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.
• [2] 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).
• [1] 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.

• 国家重点研发计划（项目骨干，负责经费100万元）2026.01 - 2028.12
• 国家重点研发计划颠覆性项目（项目骨干，负责经费220万元）2026.01 - 2027.12
• 国家自然科学基金青年科学基金项目（主持，30万元）2026.01 - 2028.12
• 国家资助博士后研究人员计划B档（36万元）2025.09 - 2026.06
• 中国博士后科学基金第77批面上资助（主持，8万元）2025.09 - 2026.06

中科院数公司经理奖学金特等奖

华罗庚奖学金

上海市优秀毕业生

期刊审稿人： IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), IEEE Transactions on Services Computing (IEEE TSC), Transactions on Machine Learning Research (TMLR), ACM Transactions on AI for Science (ACM TAIS), Machine Intelligence Research (MIR), Physics of Fluids (POF)

会议审稿人：Neural Information Processing Systems (NeurIPS), International Conference on Learning Representations (ICLR), International Conference on Machine Learning (ICML), Knowledge Discovery and Data Mining (KDD), AAAI Conference on Artificial Intelligence (AAAI)

邮箱：rayzhang@ruc.edu.cn

个人网页：https://optray.github.io/