涂一辉
职称/职务：讲师/硕士生导师
邮箱：tuyihui@shu.edu.cn
研究领域：离子输运问题中的快速算法，基于神经网络的快速求解器和相场方程的高效计算
教育经历：
2017/09 - 2023/09，上海交通大学，数学科学学院，数学，博士，导师：徐振礼教授
2021/11 - 2022/10，普渡大学，博士联合培养
2013/09 - 2017/06，上海交通大学，致远学院，数学与应用数学（交大理科班），学士
工作经历：
2023/12-至今，上海大学，数学系，讲师
学术论文（近三年）：
(1) Y. Tu, Q. Pang, H. Yang and Z. Xu, Linear-scaling selected inversion based on hierarchical interpolative factorization for self Green's function for modified Poisson Boltzmann equation in two dimensions, Journal of Computational Physics, 2022, 461: 110893.
(2) Y. Tu, Z. Xu and H. Yang, Hierarchical interpolative factorization for self Green’s function in 3D modified Poisson-Boltzmann equations, Communications on Applied Mathematics and Computation, 2025,7:536-561, In CAMC focused issue in memory of Professor Zhong-Ci Shi.
(3) L. Shi, Y. Li, K. Zeng, Y. Tu and J. Yan, Optimal flow transportand its entropic regularization: A GPU-friendly matrix iterative algorithm for flow balance satisfaction, International Conference on Learning Representations, Singapore, 2025.
(4) L. Gao, D. Zhang, Y. Chen, Y. Tu, X. Zhang and X. Li, Grid residual adaptive resampling for physics-informed neural networks to solve incompressible Navier-Stokes equations, Journal of Applied Physics, 2025, 137: 154702.
Preprints
(1) Y. Tu, H. Tian, L. Shi and Q. Zhou, SchulzNN: A neural network-based matrix inversion solver inspired by Schulz iteration. Submitted.
(2) S. Liu, Y. Tu and G. Wang, Exponential-enhanced Fourier neural operator: A dual-channel framework for solving pdes with non-local kernels. Submitted.
(3) J. Yan, L. Shi, F. Zhou, J. Liu, Z. Gui, W. Pan and Y. Tu, Design linear constrained neural layers with implicit convex optimization. Submitted.
(4) Z. Shi, Y. Tu, J. Yan and L. Shi, DB-OT: Optimal transport with double bounds and its applications in clustering, classification and beyond. Submitted.