About

I am currently an Assistant Professor at the Gaoling School of Artificial Intelligence, Renmin University of China. I received my B.S. degree from the School of Mathematical Sciences, East China Normal University in 2019, and my Ph.D. degree from the Academy of Mathematics and Systems Science, Chinese Academy of Sciences in 2024. From 2024 to 2026, I was a Postdoctoral Researcher at the Gaoling School of Artificial Intelligence, Renmin University of China. My research focuses on the theory, algorithms, and applications of intelligent scientific computing, with particular interests in integrating physical laws with deep learning for the modeling, inversion, control, and optimization of complex physical systems.

Experience

• 2026.8-Present: Assistant Professor, Gaoling School of Artificial Intelligence, Renmin University of China
• 2024.9-2026.8: Postdoctoral Researcher, Gaoling School of Artificial Intelligence, Renmin University of China
  • Supervisor: Hao Sun
• 2019.9-2024.6: Ph.D. Student, Academy of Mathematics and Systems Science, Chinese Academy of Sciences
  • Major: Probability and Mathematical Statistics
  • Supervisor: Zhi-Ming Ma
• 2022.5-2023.7: Research Intern, Microsoft Research AI4Science Asia
  • Group: Large-scale PDEs
  • Mentor: Qi Meng
• 2015.9-2019.6: B.S. in Mathematics and Applied Mathematics, East China Normal University

Grants

• 2026-2028: National Key R&D Program of China (Co-PI, responsible for ¥1 million)
• 2026-2027: National Key R&D Program of China, Disruptive Technology Project (Co-PI, responsible for ¥2.2 million)
• 2026-2028: NSFC Young Scientists Fund (PI, ¥300,000)
• 2025-2026: National Postdoctoral Fellowship Program, Tier B (¥360,000)
• 2025-2026: China Postdoctoral Science Foundation General Program (PI, ¥80,000)

Publications

Google Scholar / Full publication list

Selected and Recent Work

• 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.
• 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.
• 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. Paper / Code
• Zhang, R.*, Du, X.*, Yan, J., & Zhang, S. (2025). The Decoupling Concept Bottleneck Model. IEEE Transactions on Pattern Analysis and Machine Intelligence. Paper / Code
• Zhang, R., Meng, Q., & Ma, Z.M. (2024). Deciphering and Integrating Invariants for Neural Operator Learning with Various Physical Mechanisms. National Science Review. Paper / Code

Selected Awards

• 2026: Young Talents Program of Renmin University of China
• 2023: AMSS Special Prize of President Scholarship
• 2022: Hua Loo-Keng Scholarship
• 2019: Outstanding Undergraduate in Shanghai
• 2018: Second Prize, National Undergraduate Mathematics Contest Final
• 2016: Excellent Scholarship in ECNU

Academic Service

• Journals: IEEE TPAMI, IEEE TKDE, IEEE TSC, TMLR, ACM TAIS, Machine Intelligence Research, Physical Review Fluids, and Physics of Fluids
• Conferences: NeurIPS, ICLR, ICML, KDD, and AAAI