BIMSA > Pipi Hu
Associate Professor Pipi Hu

Group: Computational Mathematics

Office: A11-106

Email: hpp@bimsa.cn

Research Field: Large Foundation Model

Research Interest

  • Research on cutting-edge technologies in foundation models, including continuous and discrete diffusion models as well as autoregressive models.
  • The scientific foundation model for science.
  • Machine learning based on differential equations: solving operators, inverse problems, and data-driven machine learning modeling with differential equation structures.

Education Experience

  • 2014 - 2020      Tsinghua University      Mathematics      Ph.D
  • 2010 - 2014      Tsinghua University      Engineering Physics      B.Sc.

Work Experience

  • 2025 -      BIMSA      Associate Professor
  • 2022 - 2025      Microsoft Research Institute Science Intelligence Center      Senior Research Fellow      Scientific Large Model
  • 2020 - 2022      BIMSA & YMSC      Postdoc      Deep Learning and Differential Equations

Publication

  • [1] Liwei Lu, Zhijun Zeng, Yan Jiang, Yi Zhu, and Pipi Hu, Weak Collocation Regression method: fast reveal hidden stochastic dynamics from high-dimensional aggregate data, Journal of Computational Physics, 502, 112799 (2024)
  • [2] L Guo, L Lu, Z Zeng, P Hu, Y Zhu, Weak Collocation Regression for Inferring Stochastic Dynamics with L\'{e} vy Noise, arXiv preprint arXiv:2403.08292 (2024)
  • [3] Zhijun Zeng, Pipi Hu, Chenglong Bao, Yi Zhu, Zuoqiang Shi, Reconstruction of dynamical systems from data without time labels, arXiv preprint arXiv:2312.04038 (2023)
  • [4] Guochang Lin, Pipi Hu, Fukai Chen, Xiang Chen, Junqing Chen, Jun Wang, Zuoqiang Shi, BINet: Learning to Solve Partial Differential Equations with Boundary Integral Networks, CSIAM Transactions on Applied Mathematics(2023)
  • [5] P. Hu, P. Xie, Yi Zhu, Traveling edge states in massive Dirac equations along slowly varying edges, IMA Journal of Applied Mathematics, 88(3), 455-471 (2023)
  • [6] Pipi Hu, Wuyue Yang, Yi Zhu, and Liu Hong, Revealing hidden dynamics from time-series data by ODENet, Journal of Computational Physics, 461, 111203 (2022)
  • [7] Pipi Hu, Ablowitz, Mark J.,Justin T.Cole,Pipi Hu,and Peter Rosenthal, Peierls-Nabarro barrier effect in nonlinear Floquet topological insulators, Phys. Rev. E, 103(4), -, 2021(2021)
  • [8] P Hu, L Hong, Y Zhu, Linear and nonlinear electromagnetic waves in modulated honeycomb media, Studies in Applied Mathematics, 144(1), 18-45 (2020)
  • [9] G Zhang, Y Li, R Luo, P Hu, Z Zhao, L Li, G Liu, Z Wang, R Bi, K Gao, ..., Unigenx: Unified generation of sequence and structure with autoregressive diffusion, arXiv (2025)
  • [10] M Ma, G Liu, C Cao, P Deng, T Dao, A Gu, P Jin, Z Yang, Y Xia, R Luo, ..., HybriDNA: A Hybrid Transformer-Mamba2 Long-Range DNA Language Model, arXiv (2025)
  • [11] L Guo, Z Wang, C Liu, J Li, P Hu, Y Zhu, Potential Score Matching: Debiasing Molecular Structure Sampling with Potential Energy Guidance, arXiv (2025)
  • [12] MR AI4Science, MA Quantum, The impact of large language models on scientific discovery: a preliminary study using gpt-4, arXiv (2023)
  • [13] G Lin, F Chen, P Hu, X Chen, J Chen, J Wang, Z Shi, Bi-greennet: learning green’s functions by boundary integral network, Communications in Mathematics and Statistics, 11(1), 103-129 (2023)
  • [14] W Cui, H Zhang, H Chu, P Hu, Y Li, On robustness of neural ODEs image classifiers, Information Sciences, 632, 576-593 (2023)
  • [15] G Lin, F Chen, P Hu, X Chen, J Chen, J Wang, Z Shi, A neural network framework for learning Green's function

 

Update Time: 2025-07-14 14:21:18