职称

教授

电子邮件

yinglotus@shu.edu.cn

办公室

计921室

研究方向

人工智能与科学计算、数值模拟、机器学习等方面研究和应用

个人简介

李颖，博士，教授。2014年博士毕业于西安交通大学。主要研究方向为人工智能与科学计算、数值模拟、机器学习等方面的研究和应用。主持国家自然科学基金面上项目、国家自然科学基金青年基金、上海市科技英才扬帆计划、企业委托项目等多项项目。多次合作参与科技部重点研发计划。相应成果发表于《National Science Review》、《Journal of Computational Physics》、《Journal of Scientific Computing》、《Applied Mathematical Modelling》、《Computer Physics Communications》、《Nonlinear Dynamics》、《Journal of Alloys and Compounds》、《Scripta Materialia》、《Chaos, Solitons & Fractals》等国际知名顶级期刊中。

科研项目

2025-2028，国家自然科学基金面上，主持

2022-2027，科技部重点研发计划 参与

2024-2026，科技部重点研发计划 参与

2016-2019，国家自然科学基金青年基金，主持

2016-2018，上海市扬帆计划，

代表性论文或专著

[1]Yanjie Wang, Ying Li*, Yaxin Peng, Shihui Ying, Sliding physical invariant neural operator for long-term prediction of complex dynamics in physical systems, National Science Review, IF 23.178;

[2]Ying Li, Jiawei Yang, Dong Wang, Self-knowledge Distillation Enhanced Universal Framework for Physics- Informed Neural Networks, Nonlinear Dynamics, 2025; SCI; IF 5.2; 中科院工程技术2区.

[3]Yanjie Wang, Yaxin Peng, Zhaoping Hu, Ying Li*, Exploring prototype-guided strategy for domain decomposition in physics-informed neural network, Nonlinear Dynamics, 2025; SCI; IF 5.2; 中科院工程技术2区.

[4]Ying Li, Hui Shi, Xinghui Zhong, Local Discontinuous Galerkin Methods with Multistep Implicit–Explicit Time Discretization for Nonlinear Schrödinger Equations, Journal of Scientific Computing, 2024, Volume 101; IF 2.8; 中科院数学2区.

[5]Jie Hou, Ying Li*, HNS: An Efficient Hermite Neural Solver for Solving Time-Fractional Partial Differential Equations, Chaos, Solitons & Fractals, 2024, Volume 181, 114637; SCI; IF 5.3; 中科院数学1区.

[6]Dinglei Zhang , Ying Li*, Shihui Ying, Trans-Net: A transferable pretrained neural networks based on temporal domain decomposition for solving partial differential equations, Computer Physics Communications, 2024, Volume 299, 109130; SCI; IF 7.2; 中科院物理与天体物理2区.

[7]Jie Hou, Ying Li*, Shihui Ying, Iterative optimization method for determining optimal shape parameter in RBF-FD method, Applied Mathematics Letters, 2023, Volume 145, 108736; IF 2.9; 中科院数学 2区.

[8]Jie Hou, Ying Li*, Shihui Ying, Enhancing PINNs for solving PDEs via adaptive collocation point movement and adaptive loss weighting, Nonlinear Dynamics, 2023, Volume 111, pages 15233– 15261; SCI; IF 5.2; 中科院工程技术2区.

[9]Zhiying Ma, Jie Hou, Yaxin Peng, Ying Li*, PMNN: Physical Model-driven Neural Network for solving time‑fractional differential equations, Chaos, Solitons and Fractals, 2023, Volume 177, 114238; SCI; IF 5.3; 中科院数学1区.

[10]Ying Li, Zuojia Zhou, Shihui Ying, DeLISA: Deep learning based iteration scheme approximation for solving PDEs, Journal of Computational Physics, 2022, Volume 451,110884; SCI; IF 3.8;中科院 数学物理1区.